Method and device for evaluating effect of composite anesthetic, storage medium and medical equipment

Abstract

The application discloses a composite anesthetic effect evaluation method and device, a storage medium and medical equipment. The method comprises the following steps: synchronously and in real time, acquiring the administration information of inhaled anesthetic drugs and the administration information of intravenous infusion anesthetic drugs; calculating the effect site concentration of inhaled anesthetic drugs based on the administration information of inhaled anesthetic drugs and a first drug model, and calculating the effect site concentration of intravenous infusion anesthetic drugs based on the administration information of intravenous infusion anesthetic drugs and a second drug model; and calculating the composite anesthetic effect by using a joint pharmacodynamic evaluation model based on the effect site concentration of inhaled anesthetic drugs and the effect site concentration of intravenous infusion anesthetic drugs. Through the above method, the real-time quantitative evaluation of the composite anesthetic effect is realized, the administration information of different administration routes can be uniformly converted into the effect site concentration as a pharmacodynamic fusion interface and the pharmacokinetic interaction between drugs is described, the evaluation accuracy is improved, and reliable quantitative reference basis is provided for clinical anesthetic decision-making.

Description

Technical Field

[0001] This application relates to the field of clinical medical technology, and in particular to a method, device, storage medium and medical equipment for evaluating the efficacy of compound anesthetic drugs. Background Technology

[0002] In modern clinical anesthesia practice, accurate assessment and control of anesthetic efficacy are crucial for ensuring surgical safety and postoperative recovery quality. Currently, the gold standard for measuring the efficacy of inhaled anesthetics is the "Minimum Alveolar Concentration" (MAC), defined as the concentration of alveolar anesthetic that, under one atmosphere of pressure, prevents 50% of patients from producing a somatomotor response upon skin incision stimulation. This indicator provides a unified reference scale for evaluating the efficacy and regulating the administration of single inhaled anesthetics. Furthermore, with the development of anesthesia techniques, combined anesthesia is increasingly used in clinical practice, employing both inhaled and intravenous anesthetics to achieve synergistic effects such as analgesia, sedation, and muscle relaxation.

[0003] In current clinical practice, the assessment of the efficacy of combined anesthetic drugs mainly relies on the judgment of anesthesiologists based on individual experience, or on indirect assessment of the patient's central nervous system status using electroencephalogram (EEG) monitoring equipment (such as bispectral index BIS or entropy index monitors). These assessment methods have significant shortcomings in accuracy and reliability: First, the traditional concept of minimum alveolar effective concentration (MPAL) was initially proposed for single inhaled anesthetics and cannot directly quantify the total anesthetic efficacy of a mixture of multiple drugs, leading clinicians to often rely on experience for estimation, lacking a unified and intuitive quantitative standard. Second, existing methods for calculating the efficacy of combined anesthetic drugs typically use a simple linear summation method, ignoring the complex pharmacodynamic interactions (especially synergistic effects) between different types of anesthetic drugs, resulting in significant biases in the assessment of combined anesthetic efficacy and failing to meet the needs of precision medicine. Furthermore, relying on additional external equipment to monitor anesthetic efficacy is not only costly but also has poor interference resistance, increasing the complexity of clinical procedures and the medical burden. Summary of the Invention

[0004] This application provides a method, device, storage medium, and medical equipment for evaluating the efficacy of combined anesthetic drugs, aiming to solve the technical problem of insufficient accuracy in existing methods for evaluating the efficacy of combined anesthetic drugs.

[0005] To address the aforementioned technical problems, the technical solution adopted in this application is: to provide a method for evaluating the efficacy of combined anesthetic drugs. This method includes: simultaneously acquiring, in real-time, the administration information of inhaled anesthetic drugs and intravenously infused anesthetic drugs; calculating the effect-site concentration of the inhaled anesthetic drug based on the administration information of the inhaled anesthetic drug and a first drug model, and calculating the effect-site concentration of the intravenously infused anesthetic drug based on the administration information of the intravenously infused anesthetic drug and a second drug model; and calculating the combined anesthetic efficacy using a combined efficacy evaluation model based on the effect-site concentrations of the inhaled and intravenously infused anesthetic drugs.

[0006] In some embodiments, synchronously acquiring in real-time dosing information of inhaled anesthetic drugs and dosing information of intravenously infused anesthetic drugs includes: real-time acquisition of dosing data from the anesthesia machine and infusion pump; standardizing the acquired dosing data to obtain the dosing information of the inhaled anesthetic drugs and the dosing information of the intravenously infused anesthetic drugs, and synchronously outputting them to the corresponding drug model.

[0007] In some embodiments, calculating the effect-site concentration of the inhaled anesthetic drug based on the drug administration information and a first drug model includes: dividing the single inhaled anesthetic effect-site concentration update process into multiple independently schedulable calculation stages; executing each calculation stage sequentially in different scheduling cycles according to a preset scheduling order, and maintaining intermediate calculation results between scheduling cycles to achieve continuous progress across cycles; and after all the multiple calculation stages are completed, performing physical feasibility constraints and boundary restrictions on the calculation results to obtain the effect-site concentration of the inhaled anesthetic drug.

[0008] In some embodiments, before calculating the effect-site concentration of the inhaled anesthetic drug based on the administration information of the inhaled anesthetic drug and the first drug model, and before calculating the effect-site concentration of the intravenously infused anesthetic drug based on the administration information of the intravenously infused anesthetic drug and the second drug model, the method further includes: obtaining basic patient information; the basic patient information includes one or more of height, weight, age, and gender; and based on the basic patient information, individually adjusting the model parameters of the first drug model and the model parameters of the second drug model.

[0009] In some embodiments, both the first drug model and the second drug model employ a multi-compartment pharmacokinetic model; the first drug model includes alveolar compartments, multiple tissue compartments, and an effect compartment to simulate the distribution process of inhaled anesthetic drugs in the body; the second drug model includes a central compartment, at least one peripheral compartment, and an effect compartment to simulate the distribution process of intravenously infused anesthetic drugs in the body.

[0010] In some embodiments, the combined anesthetic efficacy is calculated using a combined pharmacodynamic evaluation model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug. This includes: calculating the normalized power units (NPUs) of each drug based on the effect-site concentrations of the inhaled and intravenously infused anesthetic drugs; calculating drug proportion parameters based on the normalized power units; expressing the combined effect of the inhaled and intravenously infused anesthetic drugs as a function of the normalized total drug units, and introducing maximum effect, half-effect unit (WU) parameters, and curve steepness parameters related to the drug proportion parameters to construct the combined pharmacodynamic evaluation model; wherein the maximum effect, half-effect unit (WU) parameters, and curve steepness parameters are polynomial functions of the drug proportion parameters, and satisfy the constraint that the model degenerates into a single-drug effect model when the drug proportion parameters take boundary values; and calculating the combined anesthetic efficacy based on the combined pharmacodynamic evaluation model.

[0011] In some embodiments, after calculating the combined anesthetic efficacy using a combined pharmacodynamics assessment model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, the method further includes: calculating the minimum alveolar effective concentration equivalent value based on the combined anesthetic efficacy; and determining the interaction nature between the inhaled anesthetic drug and the intravenously infused anesthetic drug based on the half-response unit parameter of the combined pharmacodynamics assessment model, wherein the interaction nature includes synergistic effects, additive effects, and antagonistic effects.

[0012] To address the aforementioned technical problems, another technical solution adopted in this application is to provide a combined anesthetic efficacy evaluation device. This device includes: a synchronous real-time data acquisition module for synchronously acquiring dosing information of inhaled anesthetic drugs and intravenous infusion anesthetic drugs; an inhaled anesthetic drug effect-site concentration calculation module for calculating the effect-site concentration of the inhaled anesthetic drug based on the dosing information and a first drug model; an intravenous infusion anesthetic drug effect-site concentration calculation module for calculating the effect-site concentration of the intravenous infusion anesthetic drug based on the dosing information and a second drug model; and a fusion efficacy calculation module for calculating the combined anesthetic efficacy using a combined efficacy evaluation model based on the effect-site concentrations of the inhaled and intravenous anesthetic drugs.

[0013] To address the aforementioned technical problems, another technical solution adopted in this application is to provide a storage medium storing program data. This storage medium includes steps for implementing the aforementioned method for evaluating the efficacy of combined anesthetic drugs when the program data is executed by a processor.

[0014] To address the aforementioned technical problems, another technical solution adopted in this application is to provide a medical device. This medical device includes a processor and a memory interconnected, the memory storing a computer program, and the processor executing the computer program to implement the steps of the aforementioned method for evaluating the efficacy of compound anesthetic drugs.

[0015] The beneficial effects of this application are as follows: Unlike existing technologies, this application discloses a method, apparatus, storage medium, and medical device for evaluating the efficacy of combined anesthetic drugs. This application simultaneously acquires the administration information of inhaled anesthetic drugs and intravenously infused anesthetic drugs in real time, and calculates their respective effect-site concentrations using a first drug model and a second drug model. Finally, based on these two effect-site concentrations, a combined pharmacodynamic evaluation model is used to calculate the efficacy of the combined anesthetic drug. Specifically, simultaneous real-time acquisition of administration information ensures that the administration data of the two heterogeneous administration pathways remain consistent in time, providing a time-aligned data foundation for subsequent pharmacodynamic fusion calculations. Calculating the effect-site concentrations using the first and second drug models respectively transforms the original administration information from different routes into a unified pharmacokinetic index representing the actual concentration of the drug at the site of action, thus establishing a comparable interface between drugs administered via different routes. Calculating the efficacy of the combined anesthetic drug based on the effect-site concentration using the combined pharmacodynamic evaluation model allows the model to characterize the pharmacodynamic interaction between inhaled and intravenously infused anesthetic drugs, avoiding the problem of excessive evaluation bias caused by neglecting drug interactions when using a simple linear summation method. Through the above methods, this application achieves real-time quantitative assessment of the efficacy of combined anesthetic drugs, improves the accuracy of the assessment, and helps to provide a reliable quantitative reference for clinical anesthesia decision-making. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Figure 1 This is a flowchart illustrating an embodiment of the method for evaluating the efficacy of compound anesthetics provided in this application; Figure 2 yes Figure 1 A schematic diagram of the structure of an embodiment of the first drug model used in step 20 of the example; Figure 3 yes Figure 1 A schematic diagram of the structure of an embodiment of the second drug model used in step 20 of the embodiments; Figure 4 yes Figure 1A schematic diagram of an embodiment of the combined drug efficacy evaluation model used in step 30 of the example; Figure 5 This is a schematic diagram of an embodiment of the compound anesthetic efficacy evaluation device provided in this application; Figure 6 This is a schematic diagram of the structure of an embodiment of the storage medium provided in this application; Figure 7 This is a schematic diagram of the structure of an embodiment of the computer device provided in this application. Detailed Implementation

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

[0018] The terms "first," "second," and "third" used in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0019] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0020] This application provides a method for evaluating the efficacy of combined anesthetic drugs, see reference. Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the combined anesthetic efficacy evaluation method provided in this application. The combined anesthetic efficacy evaluation method includes: Step 10: Simultaneously and in real-time acquire information on the administration of inhaled anesthetic drugs and intravenous infusion anesthetic drugs.

[0021] In this embodiment, inhaled anesthetic drugs refer to drugs that enter the alveoli through the respiratory tract and enter the blood circulation through gas exchange, thereby producing an anesthetic effect at sites of action such as the central nervous system. Specifically, they can be one or more of the following: ether-based halogenated anesthetics (such as sevoflurane, isoflurane, desflurane), halogenated alkyls (such as halothane), and inorganic gases (such as nitrous oxide). The corresponding dosing information is a set of parameters used to characterize the inhalation-side dosing status, ventilation / circulation status, and drug type. Specifically, it can include data fields such as inhaled anesthetic gas concentration, tidal volume, alveolar ventilation, functional residual capacity, cardiac output, and type of inhaled anesthetic drug, as well as the sampling timestamp, validity marker (e.g., device online / offline, data missing marker), and unit information corresponding to the above data fields.

[0022] In this embodiment, since the administration of inhaled anesthetic drugs is typically controlled and executed by an anesthesia machine, a communication connection can be established with the anesthesia machine to obtain relevant drug administration and physiological data using the machine's operating parameters, thereby achieving real-time acquisition of inhaled drug administration information. Specifically, the drug administration information for inhaled anesthetic drugs may include: the concentration of inhaled anesthetic gas (denoted as...). This reflects the real-time concentration of anesthetic drugs in the inhaled airway, which is controlled in real time by the anesthesia machine and can be collected by the gas concentration sensor in the breathing circuit of the anesthesia machine. Tidal volume (denoted as...) Alveolar ventilation (ALV) reflects the volume of gas inhaled or exhaled with each breath, and is also collected in real time by the anesthesia machine, serving as the basis for calculating alveolar ventilation. This reflects the actual amount of gas involved in alveolar gas exchange, which can be collected in real time by the carbon dioxide module used for carbon dioxide monitoring in the anesthesia machine; functional residual capacity (referred to as...). This reflects the amount of gas remaining in the lungs at the end of expiration, which can also be collected in real time by the carbon dioxide module of the anesthesia machine; cardiac output (referred to as...). The data includes the amount of blood pumped by the heart per minute (which can be collected in real-time by the blood oxygenation module in the anesthesia machine) and the type of inhaled anesthetic drug (i.e., the currently used inhaled anesthetic drug, which can be obtained directly from the drug selection information of the anesthesia machine or manually entered and confirmed by medical staff). This information on the administration of inhaled anesthetic drugs comprehensively reflects the dynamic distribution of inhaled anesthetic drugs in the patient's respiratory and circulatory systems. By inputting these parameters into the first drug model, which will be introduced later, the real-time concentration of inhaled anesthetic drugs in the effect room can be accurately calculated, providing precise inhalation-side input variables for subsequent composite pharmacodynamic assessments.

[0023] In this embodiment, intravenously infused anesthetic drugs refer to drugs that are injected into the body through veins and reach the central nervous system and other sites of action through blood circulation, thereby producing an anesthetic effect. Specifically, they can be one or more of the following drugs: sedative-hypnotic drugs (such as propofol), opioid analgesics (such as fentanyl, sufentanil, remifentanil), dissociative anesthetics (such as ketamine), benzodiazepines (such as midazolam), or receptor agonists (such as dexmedetomidine). The corresponding dosing information is information that characterizes the intravenous anesthetic drug infusion status and related physiological parameters of the patient. Specifically, it can include data fields such as infusion rate and type of infused drug, as well as the sampling timestamp, validity marker (such as device online / offline, data missing marker), and unit information corresponding to the above data fields.

[0024] In this embodiment, since the administration of anesthetic drugs via intravenous infusion is typically controlled and executed by an infusion pump, a communication connection can be established with the infusion pump to obtain relevant infusion data using the pump's operating parameters, thereby achieving real-time acquisition of intravenous drug administration information. Specifically, the drug administration information for intravenous anesthetic drugs may include: infusion rate (denoted as...). This reflects the infusion volume of intravenous anesthetic drugs per unit time, which is controlled and collected in real time by the infusion pump, and the type of infused drug (i.e., the type of intravenous anesthetic drug currently in use, which can be obtained directly from the drug channel configuration information of the infusion pump, or can be manually entered and confirmed by medical staff).

[0025] In this embodiment, real-time acquisition of inhalation and intravenous dual-channel drug administration data can be achieved by instantly triggering or periodically polling the operating parameters of the corresponding anesthesia machine and infusion pump. To ensure the accuracy of subsequent pharmacodynamic fusion calculations, it is also necessary to ensure the synchronization of data collected from heterogeneous devices. Specifically, the drug administration information for inhaled anesthetics must be consistent with the drug administration information for intravenously infused anesthetics on the same timeline to avoid situations where the input data from the inhalation and intravenous sides belong to different time segments due to different refresh rhythms of different peripherals. To achieve data synchronization, heterogeneous multi-source data can be mapped to the same timeline through methods such as unified sampling clocks, timestamp alignment, or synchronous caching, thereby ensuring the temporal consistency of the input data. Furthermore, the sampling timestamp in the drug administration information can be used together with the corresponding concentration or rate data as input for subsequent dynamic calculation of effect-site concentrations, accurately reflecting the impact of the drug administration time series on drug distribution in vivo, further ensuring the accuracy and real-time nature of the combined anesthetic efficacy assessment.

[0026] This embodiment, through the synchronous real-time acquisition of inhaled and intravenously administered anesthetic drug dosing information, ensures that the dosing data from the two heterogeneous dosing pathways remain consistent in time, providing a time-aligned data foundation for subsequent pharmacodynamic fusion calculations. This improves the accuracy and reliability of combined anesthetic efficacy assessment while reducing reliance on additional external monitoring equipment. Furthermore, the modular data acquisition method allows this solution to support arbitrary combinations of various inhaled and intravenously administered anesthetic drugs. Subsequently, corresponding pharmacokinetic and pharmacodynamic parameters can be invoked for different drug combinations, expanding the clinical applicability. In addition, the inhaled and intravenously administered anesthetic drugs in this application are not limited to the specific drug types mentioned above. They can be extended to other anesthetic drugs with similar pharmacokinetic characteristics according to clinical needs. Specifically, a drug model database can be introduced, and corresponding pharmacokinetic and pharmacodynamic parameters can be configured and stored in this database. These parameters can be determined from clinical data fitting or literature review, thereby supporting the combined anesthetic efficacy assessment of more drug combinations and further enhancing the flexibility and scalability of the combined anesthetic efficacy assessment method.

[0027] Optionally, in some embodiments, the administration information of inhaled anesthetic drugs and intravenous infusion anesthetic drugs is acquired synchronously in real time, including: real-time acquisition of administration data from the anesthesia machine and infusion pump; standardization processing of the acquired administration data to obtain administration information of inhaled anesthetic drugs and intravenous infusion anesthetic drugs, and synchronous output to the corresponding drug model.

[0028] In this optional embodiment, a specific implementation method is provided to achieve data synchronization and standardization through standardized processing. Specifically, during real-time data acquisition, raw drug administration data from the anesthesia machine and infusion pump are first acquired in real time. Using the communication interfaces of each device, multi-source heterogeneous data can be obtained. However, since this drug administration data comes from external devices of different manufacturers or models, there may be differences in transmission protocols, inconsistent data refresh frequencies, and inconsistent units. The directly acquired raw data cannot be directly used for subsequent pharmacokinetic model calculations. Therefore, it is necessary to standardize the raw data to transform it into a standard input that the model can recognize.

[0029] In this optional embodiment, the standardization process may specifically include data processing steps such as timestamp alignment, outlier filtering, and validity marking. Timestamp alignment refers to adding a system-level timestamp to the data reported by each device according to a unified sampling clock cycle, or mapping the data to the most recent standard sampling time based on its acquisition time. This eliminates time deviations caused by communication delays between different devices, ensuring time consistency of dual-channel data. Outlier filtering involves removing or smoothing jump data that significantly exceeds the reasonable range or device measurement range, preventing single-point sensor noise or communication interference from impacting model solving and improving the quality of input data. Validity marking involves determining the reliability of current data based on device communication status and data quality indicators. By attaching a validity flag to the data, the model can be instructed to maintain the previous valid state or trigger an alarm when the data is invalid. Furthermore, standardization processing can also introduce unit conversion, data completion, filtering, and noise reduction operations. As long as the heterogeneous raw data can be transformed into a unified standardized format through this standardization process, it is understandable that it falls within the scope of protection of this application. By completing the above standardization processing within one sampling cycle, the quality and availability of data can be effectively improved, providing a reliable foundation for subsequent model calculations.

[0030] In this optional embodiment, to ensure the synchronization of the calculation starting points for different drug pathways, the standardized dosing information also needs to be synchronously output to the corresponding drug model, thereby ensuring that the model calculations for the inhalation side and the intravenous side are based on input data from the same time segment. Through this standardization and synchronous output mechanism, a standard input snapshot for the corresponding sampling period can be formed, providing a consistent and reliable data foundation for subsequent concentration calculations and pharmacodynamic fusion. This synchronous real-time data acquisition mechanism not only avoids the time segment misalignment problem caused by different refresh rhythms of heterogeneous data, but also significantly improves the consistency and accuracy of real-time evaluation of combined anesthetic efficacy.

[0031] Step 20: Calculate the effect-site concentration of the inhaled anesthetic drug based on the administration information of the inhaled anesthetic drug and the first drug model, and calculate the effect-site concentration of the intravenously infused anesthetic drug based on the administration information of the intravenously infused anesthetic drug and the second drug model.

[0032] In this embodiment, based on the simultaneous real-time acquisition of administration information for inhaled and intravenously infused anesthetic drugs in step 10, the effect-site concentrations of both inhaled and intravenously infused anesthetic drugs will be calculated simultaneously in real time. The effect-site concentration is the actual concentration of the drug at its site of action (such as central nervous system receptors), and is a direct indicator of the drug's pharmacological effect. It overcomes the hysteresis effect present when relying solely on administered concentration or blood drug concentration to assess efficacy.

[0033] In this embodiment, the calculation process specifically introduces a first drug model and a second drug model to solve pharmacokinetic problems. These two drug models can specifically adopt different compartment models (such as a single-compartment model, a two-compartment model, a three-compartment model, or a multi-compartment model with ≥4 tissue compartments, etc.). The compartment model is used to simulate the absorption, distribution, metabolism, and excretion of drugs in the human body, thereby unifying the dosing information of different routes of administration into comparable effect compartment concentrations, and establishing a unified input interface for subsequent pharmacodynamic fusion calculations. In this embodiment, the first drug model is the pharmacokinetic model used to calculate the effect-site concentration of inhaled anesthetic drugs, while the second drug model is the pharmacokinetic model used to calculate the effect-site concentration of intravenously infused anesthetic drugs. In practice, a suitable compartmental model structure is typically selected based on the route of administration and drug characteristics of the corresponding anesthetic method. For example, the first drug model can use a suitable five-compartment model for dynamic closed-loop solution based on the pharmacokinetic behavior of inhaled anesthetic drugs, which exhibit complex tissue distribution and accumulation characteristics in vivo. The second drug model, on the other hand, uses a classic three-compartment model for calculation based on the pharmacokinetic behavior of intravenously infused anesthetic drugs, which directly enter the bloodstream and distribute between the central and peripheral compartments. Through parallel calculation of these dual-channel heterogeneous models, real-time and accurate reconstruction of the concentration at the site of action of drugs from two different administration routes can be achieved, laying the foundation for pharmacodynamic fusion of heterogeneous administration pathways.

[0034] Optionally, in some embodiments, calculating the effect-site concentration of the inhaled anesthetic drug based on the drug administration information and a first drug model includes: dividing the single inhaled anesthetic effect-site concentration update process into multiple independently schedulable calculation stages; executing each calculation stage sequentially in different scheduling cycles according to a preset scheduling order, and maintaining intermediate calculation results between scheduling cycles to achieve continuous progress across cycles; and after all multiple calculation stages are completed, performing physical feasibility constraints and boundary restrictions on the calculation results to obtain the effect-site concentration of the inhaled anesthetic drug.

[0035] In this optional embodiment, an asynchronous time-sharing scheduling mechanism is provided for calculating the effect-room concentration of inhaled anesthetic drugs. Specifically, since the process of solving for the effect-room concentration of inhaled anesthesia involves multiple steps such as multi-compartment state updates, parameter corrections, numerical integration, and result constraints, completing all calculations at once within a single calculation cycle can easily lead to excessive instantaneous computational load, thereby affecting the normal execution of subsequent real-time tasks such as display refresh, alarm response, device communication, and parallel calculations for intravenous anesthesia channels. Therefore, this optional embodiment sets up an asynchronous time-sharing calculation mechanism to break down a single update process of the effect-room concentration of inhaled anesthesia into multiple independently schedulable calculation stages, and gradually completes a complete update within multiple scheduling cycles. The core idea of ​​this mechanism is that after acquiring new input data in each sampling cycle, instead of immediately executing a full round of centralized calculation, the input information required for this round of calculation is first latched, and then the scheduler processes it sequentially within multiple shorter task cycles according to a predetermined order.

[0036] In this optional embodiment, during the asynchronous time-sharing computation, the single inhalation anesthesia effect room concentration update process can be divided into multiple independently schedulable computation stages, such as parameter update stage, state construction stage, integral advancement stage, result synthesis stage, and boundary constraint stage. Each scheduling preferably executes only one stage or a portion of that stage, thereby distributing the large-scale computation across multiple time slots and reducing the peak load of a single scheduling. After each computation stage is executed sequentially, the intermediate state, intermediate derivatives, temporary calculation results, and stage advancement information of the current round of tasks must be maintained between scheduling cycles. This allows subsequent stages to continue execution based on the results of the previous stage without restarting the entire round of computation, thus achieving continuous time-sharing computation across cycles. Once all the above calculation stages are completed, the state results obtained from this round of updates are uniformly checked and post-processed. This includes implementing physical feasibility constraints (to ensure that the calculation results conform to physical laws, such as constraining the concentration to be negative and the total amount of drug in each tissue compartment to not exceed the total amount of drug administered), boundary restrictions (to reasonably limit the range of calculation results based on actual physiological conditions to avoid unreasonable values, such as limiting the effect room concentration to not exceed the maximum allowable concentration or the concentration change rate to be within the physiologically reasonable range), state write-back (saving the currently calculated state variables to the global storage area for the next round of calculation), and derivative quantity update (recalculating the relevant intermediate variables based on the updated state variables), etc. The final obtained inhalation anesthesia effect room concentration is then output to the subsequent fusion pharmacodynamics calculation module, thereby ensuring the reliability and stability of the output results.

[0037] In this optional embodiment, to implement the above-mentioned asynchronous time-sharing calculation mechanism, multiple functional units (including a task initiation unit, a stage scheduling unit, an intermediate result retention unit, and a result submission unit) can work together to achieve cross-cycle scheduling of the highly complex inhalation-side calculation process. Specifically, the task initiation unit is used to generate a new round of inhalation anesthesia concentration update task after receiving the synchronous input data of the current cycle, and save the input parameters, time information, and initial state required for this round of task; the stage scheduling unit is used to divide the entire round of inhalation anesthesia effect room concentration calculation task into multiple calculation stages according to a preset scheduling order, and execute them sequentially at different scheduling times; the intermediate result retention unit is used to maintain the intermediate state, intermediate derivatives, temporary calculation results, and stage progress information of the current round of task between each scheduling cycle; the result submission unit is used to perform unified inspection and post-processing of the state results obtained in this round of update after all stages are completed, including executing physical feasibility constraints, boundary restrictions, state write-back, and derivative quantity updates, and outputting the final obtained inhalation anesthesia effect room concentration to the subsequent fusion pharmacodynamics calculation module. These functional units can be software threads, hardware timer interrupt service routines, or state machines. Through the coordinated scheduling and data interaction of these functional units, the computational tasks can be flexibly split and executed continuously across cycles. This ensures the up-to-dateness of the input data source and avoids the concentrated occupation of the controller's computing resources by high-complexity models, thereby improving the overall stability of operation.

[0038] This optional embodiment, through the aforementioned asynchronous time-sharing computation mechanism, can transform the highly complex process of calculating inhaled anesthetic concentrations into a low-peak task flow suitable for real-time operation of the medical device controller without sacrificing model accuracy. This balances computational accuracy, system real-time performance, and overall stability, while avoiding concentrated consumption of controller computing resources by the highly complex model. Furthermore, a similar optimization strategy can be employed to calculate the effect-site concentration of intravenously infused anesthetic drugs, transforming the highly complex process of calculating intravenous anesthetic concentrations into a low-peak task flow suitable for real-time operation of the medical device controller, thereby balancing computational accuracy and system real-time performance.

[0039] Optionally, in some embodiments, before calculating the effect-site concentration of the inhaled anesthetic drug based on the administration information of the inhaled anesthetic drug and the first drug model, and calculating the effect-site concentration of the intravenously infused anesthetic drug based on the administration information of the intravenously infused anesthetic drug and the second drug model, the method further includes: obtaining basic patient information; the basic patient information includes one or more of height, weight, age, and gender; and based on the basic patient information, individually adjusting the model parameters of the first drug model and the model parameters of the second drug model.

[0040] In this optional embodiment, a method for individualized adjustment of model parameters based on patient baseline information is provided. Patient baseline information is a set of parameters reflecting the individual physiological characteristics of a patient, encompassing individualized physiological data such as height, weight, age, and gender. This data can serve as the basis for correcting pharmacokinetic parameters and estimating initial cardiac output. This patient baseline information can be obtained by medical staff inputting it into the anesthesia machine, or through methods such as importing it via a hospital information system interface, scanning patient identification codes, or data synchronization between devices. This individualized data can effectively compensate for errors caused by group average parameters, improving the accuracy of pharmacokinetic fitting for patients with different physical conditions.

[0041] In this optional embodiment, since there are significant differences in drug distribution volume, metabolic rate, and hemodynamic status among different individuals, and the aforementioned patient baseline information is usually the key factor determining these differences, for example, height and weight are usually directly related to lean body weight (LBW) and cardiac output. Under normal conditions, patients with larger lean body weight have higher initial cardiac output values, and cardiac output directly affects the rate of drug transport and distribution in the body. Age usually affects the metabolic clearance rate of drugs, and the clearance rate of elderly patients is often lower. Gender mainly affects the drug distribution volume by influencing body fat percentage and lean body weight ratio. Therefore, in order to improve the model prediction accuracy, the key parameters in the model can be specifically modified based on this baseline information so that the model output is more in line with the actual physiological state of the patient. Specifically, the individualized adjustment methods include, but are not limited to, parameter optimization methods such as cardiac output estimation correction, distribution volume scaling, and elimination rate constant adjustment. By introducing patient baseline information to calibrate standard parameters, accurate effect-site concentration predictions can still be obtained when different patients are using the same drug. This application is not limited to the specific parameter adjustment formulas or adjustment objects mentioned above. Any scheme that can adaptively adjust model parameters using patient baseline information can be included in the scope of protection of this application.

[0042] This optional embodiment effectively eliminates the bias caused by individual physiological differences in pharmacokinetic calculations through the individualized adjustment mechanism based on patient basic information, and improves the applicability and robustness of the combined anesthetic efficacy assessment method in different patient groups, thereby providing a more accurate and reliable individualized quantitative reference for clinical anesthesia decision-making.

[0043] Optionally, in some embodiments, both the first drug model and the second drug model employ a multi-compartment pharmacokinetic model; the first drug model includes alveolar compartments, multiple tissue compartments, and an effect compartment to simulate the distribution process of inhaled anesthetic drugs in the body; the second drug model includes a central compartment, at least one peripheral compartment, and an effect compartment to simulate the distribution process of intravenously infused anesthetic drugs in the body.

[0044] In this optional embodiment, a multi-compartment pharmacokinetic model is introduced as a specific implementation of the first and second drug models described above, to accurately simulate the dynamic flow of the drug in vivo and accurately reflect the hysteresis characteristics of the effect-compartment concentration. Specifically: The first drug model used to simulate the distribution of inhaled anesthetic drugs in the body specifically includes alveolar compartments, multiple tissue compartments, and effect chambers to comprehensively depict the dynamic process of drugs entering the bloodstream from the respiratory tract and gradually distributing to tissues throughout the body. The alveolar compartments are the entry points for drugs into the body via the respiratory tract, representing the gas volume and concentration state of the lungs—the core site of gas exchange during inhaled anesthesia. Their concentration changes are directly affected by ventilation and cardiac output. Tissue compartments are physiological tissue groups divided according to differences in blood perfusion rate, used to simulate the distribution and accumulation of drugs throughout the body. They typically need to be divided into multiple compartments with different perfusion characteristics to precisely depict the different effects of highly perfused and poorly perfused tissues on the time course of drug concentration. The effect chamber is a virtual site of action where the drug produces its pharmacological effect; its concentration change lags behind arterial blood concentration. Because the effect chamber is a virtual mathematical concept introduced to compensate for the lag between blood drug concentration and drug effect, rather than a real physiological anatomical chamber, it is not counted in the physical compartment count. This multi-compartment structure enables the conversion of real-time drug delivery parameters from the inhalation side into effect-compartment concentrations that reflect the actual efficacy of the drug in the central nervous system, thereby eliminating the phase difference between blood drug concentration and efficacy and providing precise input for subsequent fusion.

[0045] The second drug model used to simulate the in vivo distribution of intravenously infused anesthetic drugs specifically includes a central compartment, at least one peripheral compartment, and an effect compartment to accurately describe the distribution and elimination kinetics of intravenously administered drugs between the central and peripheral compartments after direct entry into the bloodstream. The central compartment represents the blood and highly perfused tissues where the drug initially distributes after entering the body, such as the heart, lungs, and kidneys. The peripheral compartment represents the slower-flowing superficial or deep tissues, such as muscles and fat, and at least one of these is required to describe the distribution and reflux of the drug from the central compartment to the peripheral compartment. The effect compartment is a virtual site of action driven by the concentration in the central compartment and is not counted in the physical compartment count. This multi-compartment structure accurately describes the multi-compartmental kinetics of intravenously administered drugs in vivo and the delay in their transfer to the effect compartment, thus providing a lag-free concentration indicator for evaluating the efficacy of intravenous anesthetics.

[0046] Optionally, in some embodiments, the first drug model is a five-compartment model, which includes an alveolar compartment, a vascularized tissue compartment, a muscle tissue compartment, an adipose tissue compartment, an anemic flow tissue compartment, and a first virtual effect compartment.

[0047] This optional embodiment uses the calculation of the effect-site concentration of inhaled anesthetic drugs using a five-compartment model as an example for illustration. For details, please refer to [link to relevant documentation]. Figure 2 The five-compartment model specifically includes four tissue compartments: the vascularized group (VRG), the muscle group, the adipose tissue, and the very poor group (VPG). The VRG compartment represents highly perfused tissues such as the brain, heart, liver, and kidneys, where drugs rapidly reach equilibrium. The VPG compartment, representing muscles and skin, is a large but moderately perfused compartment and is the primary site for intermediate drug distribution. The VPG compartment exhibits a strong accumulation effect on lipid-soluble inhaled anesthetics, with a low perfusion rate but a large accumulation volume, significantly affecting recovery time after prolonged drug administration. The VPG compartment represents low-perfused tissues such as bones and ligaments, where drug distribution is minimal and extremely slow. By differentially modeling these physiological tissues with different blood perfusion rates and tissue volumes, and constructing a five-compartment model by combining alveolar compartments and the first virtual effect chamber, the dynamic closed-loop distribution process of inhaled anesthetics in the human body can be highly reproduced. In particular, the accumulation effect of drugs in adipose tissue and its influence on the concentration in the effect chamber can be accurately characterized, thereby significantly improving the accuracy and timeliness of inhaled anesthetic efficacy assessment.

[0048] In this optional embodiment, based on the five-compartment model, the effect-compartment concentration of the corresponding inhaled anesthetic drug is calculated, which may specifically include: (1) Construct the differential equation for the concentration change in the alveolar compartments; The alveolar compartment is the first point of entry for inhaled anesthetic drugs into the body, and its concentration changes are determined by the drug concentration in the inhaled gas, alveolar ventilation, functional residual capacity, and blood uptake. The differential equation for the concentration changes in the alveolar compartment is as follows (denoted as Equation 1): ; in, The partial pressure concentration of the anesthetic gas in the alveoli (unit: vol% or atm) is one of the core variables that needs to be solved in this step, reflecting the real-time concentration level of the drug in the alveoli. The concentration of inhaled anesthetic gas (unit: vol% or atm) is controlled and collected in real time by the anesthesia machine. It is the input variable of this model and reflects the real-time concentration of anesthetic in the inhaled gas path. Alveolar ventilation (unit: L / min) reflects the actual amount of gas involved in alveolar gas exchange. It can be collected in real time by the carbon dioxide module of the anesthesia machine or calculated by subtracting dead space ventilation from tidal volume. Cardiac output (unit: L / min) reflects the amount of blood pumped by the heart per minute. It can be collected in real time by the blood oxygenation module of the anesthesia machine or estimated based on the patient's basic information. The concentration of anesthetic drugs in arterial blood (unit: mL / dL or vol%) is calculated from alveolar concentration and blood-gas partition coefficient. The concentration of anesthetic drugs in the mixed venous blood (unit: mL / dL or vol%) is calculated as a weighted average of the blood returning from each tissue compartment. Functional residual capacity (unit: L) reflects the amount of gas remaining in the lungs at the end of expiration. It can be collected in real time by the carbon dioxide module of the anesthesia machine or estimated through the patient's basic information. Time (unit: min) is the independent variable of the differential equation.

[0049] The physical meaning of this differential equation is: the rate of change of drug concentration in the alveoli equals the amount of drug carried in by ventilation per unit time minus the amount of drug carried away by the blood, divided by the alveolar volume. This item represents the net amount of drug entering the alveoli through alveolar ventilation. The item represents the net amount of drug carried away from the alveoli through blood circulation.

[0050] (2) Determine the relationship between arterial blood drug concentration and alveolar concentration; There is a balance between the concentration of anesthetic drugs in arterial blood and their concentration in the alveoli, a balance determined by the blood-gas partition coefficient. The formula for calculating the drug concentration in arterial blood is as follows (denoted as Formula 2): ; in, This indicates the concentration of anesthetic drugs in arterial blood (unit: mL / dL or vol%). The blood-gas partition coefficient (dimensionless) is the ratio of drug concentrations when the drug is distributed in equilibrium between the blood and gas phases. This parameter is determined by the type of drug and is a known constant. Different inhaled anesthetic drugs have different blood-gas partition coefficients. For example, the blood-gas partition coefficient of sevoflurane is about 0.65, that of isoflurane is about 1.4, and that of desflurane is about 0.45. This indicates the partial pressure concentration of anesthetic gas in the alveoli (unit: vol% or atm).

[0051] This formula shows that, under equilibrium conditions, the drug concentration in arterial blood is directly proportional to the alveolar concentration; the proportionality coefficient is the blood-gas partition coefficient. A larger blood-gas partition coefficient indicates higher drug solubility in the blood, stronger blood uptake of the drug, and slower anesthesia induction and recovery.

[0052] (3) Calculate alveolar ventilation; Alveolar ventilation refers to the effective ventilation volume (gas flow rate per unit time) actually involved in alveolar gas exchange, which is equal to minute ventilation minus dead space ventilation. The formula for calculating alveolar ventilation is as follows (denoted as Formula 3): ; in, This represents alveolar ventilation (unit: L / min). The dot above the variable indicates that the physical quantity is the flow rate (i.e., velocity) per unit time. Minute ventilation (unit: L / min) is equal to tidal volume multiplied by respiratory rate; The dead space ventilation (unit: L / min) is equal to the anatomical dead space volume multiplied by the respiratory rate.

[0053] The formula for calculating minute ventilation is as follows (denoted as Formula 4): ; in, Minute ventilation (unit: L / min); Tidal volume (unit: L) is measured and collected in real time by the anesthesia machine; Respiration rate (unit: breaths / min) is measured and collected in real time by the anesthesia machine.

[0054] The formula for calculating dead space ventilation is as follows (denoted as Formula 5): ; in, Indicates dead space ventilation (unit: L / min); The volume of anatomical dead space (unit: L) can be estimated by the patient's weight, and is generally taken as 2.2 mL / kg; Represents respiratory rate (unit: breaths / min).

[0055] Combining the above formulas, alveolar ventilation can also be directly expressed as (denoted as Formula 6): ; This formula shows that alveolar ventilation is equal to effective tidal volume (tidal volume minus dead space volume) multiplied by respiratory rate.

[0056] (4) Construct a formula for calculating drug concentration in mixed venous blood; Mixed venous blood refers to blood returning from all tissues of the body to the right atrium. Its drug concentration is determined by the weighted average of the blood returning from each tissue compartment. The formula for calculating the drug concentration in mixed venous blood is as follows (denoted as Formula 7): ; in, This indicates the concentration of anesthetic drugs in mixed venous blood (unit: mL / dL or vol%). This indicates blood flow to highly vascularized tissues (unit: L / min), which accounts for approximately 75% of cardiac output. This represents blood flow to muscle tissue (unit: L / min), which accounts for approximately 18.1% of cardiac output. This indicates blood flow to adipose tissue (unit: L / min), which accounts for approximately 5.4% of cardiac output. This indicates the blood flow to anemic tissues (unit: L / min), which accounts for approximately 1.5% of cardiac output. This indicates the drug concentration in venous blood flowing from highly vascularized tissues (unit: mL / dL or vol%). Indicates the drug concentration in venous blood flowing out of muscle tissue (unit: mL / dL or vol%). Indicates the concentration of drug in venous blood flowing out of adipose tissue (unit: mL / dL or vol%). This indicates the concentration of the drug in the venous blood flowing out of the anemic tissue (unit: mL / dL or vol%). This indicates cardiac output (unit: L / min).

[0057] The physical meaning of this formula is: the drug concentration in the mixed venous blood is equal to the blood flow-weighted average of the drug concentration in the blood returning from each tissue.

[0058] (5) Determine the relationship between blood flow to each tissue and cardiac output; Blood flow to each tissue is directly proportional to cardiac output, and the proportionality coefficient is determined by the tissue's perfusion characteristics. The formula for calculating blood flow to each tissue is as follows (denoted as Formula 8): ; in, Indicates the first Blood flow to each tissue (unit: L / min) ; Indicates the first The ratio of blood flow to cardiac output in a given tissue (dimensionless), for highly vascularized tissues. For muscle tissue For adipose tissue For anemic tissue 5; CO represents cardiac output (unit: L / min).

[0059] (6) Calculate the individualized estimate of cardiac output; Cardiac output is a crucial parameter affecting drug distribution, and its value varies among individual patients. This embodiment calculates lean body mass based on the patient's baseline information (height, weight, gender) and then estimates cardiac output for individualized adjustment. The formula for calculating lean body mass is as follows: For male patients (referred to as Formula 9): ; For female patients (denoted as Formula 10): ; in, Lean body mass (unit: kg) refers to body weight after fat removal and is closely related to the volume of distribution of drugs. Weight (unit: kg) is input by medical staff; The height (unit: m) is input by medical staff. Both formulas above are the standard form of James's lean body mass formula, where 6680 in the denominator for men and 8878 in the denominator for women are empirical constants, and 216 is the height coefficient, which is also obtained empirically.

[0060] The formula for estimating cardiac output is as follows (denoted as Formula 11): ; in, Cardiac output (unit: L / min); 55 represents the lean body mass (unit: kg); 55 represents the reference value for lean body mass in a standard adult (unit: kg); 5 represents the reference value for cardiac output in a standard adult (unit: L / min); 0.75 is an empirical index that reflects the non-linear relationship between cardiac output and lean body mass.

[0061] This formula shows that cardiac output is proportional to the 0.75th power of lean body mass, which can well reflect the differences in cardiac output among patients of different body types.

[0062] (7) Construct differential equations for the concentration changes in each tissue compartment; The concentration changes in each tissue compartment are determined by tissue blood flow, tissue volume, tissue / blood partition coefficient, and the concentration difference between arterial blood and venous blood in the tissue. The differential equations for the concentration changes in each tissue compartment are as follows (denoted as Equation 12): ; in, This represents the drug concentration in the venous blood flowing out of the i-th tissue (unit: mL / dL or vol%). Indicates the first Blood flow to each tissue (unit: L / min); Indicates the first The volume of an individual tissue (in liters) can be estimated using basic patient information. Indicates the first The tissue / blood partition coefficient (dimensionless) of a tissue is the ratio of drug concentrations when the drug is distributed in equilibrium between the tissue and blood phases. This parameter is determined by both the type of drug and the tissue type and is a known constant. This indicates the concentration of anesthetic drugs in arterial blood (unit: mL / dL or vol%). Indicates time (unit: min).

[0063] The physical meaning of this differential equation is: the rate of change of drug concentration within a tissue equals the amount of drug carried into the tissue by the bloodstream per unit time minus the amount carried out, divided by the effective distribution volume of the tissue. Wherein, Indicates the first The effective distribution volume of a tissue reflects the apparent distribution space of the drug in that tissue.

[0064] The parameter values ​​differ for different tissue compartments; for example, in highly vascularized tissue (VRG): (Approximately 10% of body weight) (Close to blood); Muscle tissue: (Approximately 50% of body weight) (Varies depending on the medication); Adipose tissue (Fat): (It varies from person to person) (Lipid-soluble drugs have extremely high solubility in fat); VPG (Very vascular pneumothorax): , .

[0065] (8) Construct the differential equation for the concentration change in the effect room; The effect commissure is a virtual site of action where a drug produces its pharmacological effect. Its concentration change is driven by the difference between arterial blood concentration and effect commissure concentration, and its hysteresis effect across the blood-brain barrier is described by a first-order rate constant. The differential equation for the effect commissure concentration change is as follows (denoted as Equation 13): ; in, The effect-site concentration of the inhaled anesthetic drug (unit: mL / dL or vol%) is the final output variable that needs to be solved in this step. The elimination rate constant (unit: 1 / min) represents the rate at which the drug is eliminated from the first virtual effect chamber. This parameter is determined by the type of drug and is a known constant; different inhaled anesthetics have different rates of elimination. value; This indicates the concentration of anesthetic drugs in arterial blood (unit: mL / dL or vol%). Indicates time (unit: min).

[0066] The physical meaning of this differential equation is: the rate of change of effect-site concentration is directly proportional to the difference between arterial blood concentration and effect-site concentration, with a proportionality constant of... When the arterial blood concentration is higher than the effect-site concentration, the effect-site concentration increases; conversely, it decreases. The larger the value, the faster the effect-site concentration follows the arterial blood concentration, and the smaller the hysteresis effect.

[0067] (9) Solve the system of differential equations using numerical integration.

[0068] The above formulas (1), (12), and (13) constitute a system of ordinary differential equations, describing the dynamic distribution process of inhaled anesthetic drugs in a five-compartment model. Since this system of equations has no analytical solution, a numerical integration method is required. Specifically, this embodiment uses the fourth-order Runge-Kutta method (also known as the RK4 step method) for numerical integration. This method has high numerical accuracy and stability, and is suitable for solving ordinary differential equation systems with relatively low rigidity.

[0069] The calculation steps for the fourth-order Runge-Kutta method are as follows: For ordinary differential equations of general form From time arrive The integration steps are as follows: ; ; ; ; ; in, This represents the integration step size (unit: min), typically between 0.1 and 0.5 min. express The state variable vector at time t, including Equal variables; The derivative function representing the state variable is defined by the aforementioned differential equation. Using the numerical integration method described above, the effect-site concentration of the inhaled anesthetic drug can be calculated in real time. This provides inhalation-side input variables for subsequent evaluation of the efficacy of combined anesthetic drugs.

[0070] This optional embodiment achieves real-time calculation of the effect-site concentration of inhaled anesthetic drugs based on a five-compartment model through the above calculation steps. This five-compartment model fully considers the physiological characteristics of inhaled anesthetic drug distribution in vivo, including the influence of alveolar ventilation, perfusion differences in different tissues, the accumulation effect of adipose tissue, and the hysteresis characteristics of the effect compartment. It can accurately reflect the real-time concentration of inhaled anesthetic drugs at the site of action, providing precise inhalation-side input for the evaluation of combined anesthetic drug efficacy.

[0071] Optionally, in some embodiments, the second drug model is a three-compartment model, which includes a central compartment, a second compartment, a third compartment, and a second virtual effect compartment.

[0072] This optional embodiment is specifically illustrated by using a three-compartment model to calculate the effect-compartment concentration of intravenously infused anesthetic drugs. For details, please refer to [link to relevant documentation]. Figure 3 This three-compartment model divides the in vivo process of intravenously infused drugs into a central compartment, a second compartment (a shallow peripheral compartment), a third compartment (a deep peripheral compartment), and a second virtual effect compartment. The central compartment represents blood and blood-rich organs, and is the site where intravenously infused drugs directly enter. The second and third compartments represent peripheral tissues with different perfusion rates, used to describe the distribution of drugs from the central compartment to the periphery and the return flow from the periphery to the central compartment. During the calculation, the concentration change in the central compartment is determined by the amount of drug input at the infusion rate, the amount of drug cleared from the central compartment, and the amount of transport between the central compartment and the second and third compartments. The concentration in the second virtual effect compartment is driven by the concentration in the central compartment, and its hysteresis effect across the blood-brain barrier is described by a first-order rate constant. This three-compartment model can accurately reflect the rapid distribution and slow elimination characteristics of intravenous anesthetics in vivo, and output the effect compartment concentration synchronously with the drug's efficacy in real time.

[0073] In this optional embodiment, based on the three-compartment model, the effect-compartment concentration of the corresponding intravenously infused anesthetic drug is calculated, which may specifically include the following steps: (1) Construct the differential equation for the concentration change in the central chamber; The central compartment is the first site of distribution for intravenously infused drugs after they enter the body, and its concentration changes are determined by the infusion rate, elimination rate, and transport rate with the peripheral compartments. The differential equation for the concentration change in the central compartment is as follows (denoted as Equation 14): ; in, Indicates the drug concentration in the central chamber (unit: or ), is one of the core variables that needs to be solved in this step; Inflation rate (unit: or The data is controlled and collected in real time by the infusion pump and is the input variable of this model; The volume of the central compartment (unit: L) represents the apparent distribution space of the drug within the central compartment. Represents the elimination rate constant from the central chamber (unit: This reflects the rate at which drugs are eliminated from the body; The distribution rate constant from the central chamber to the second chamber (unit: ); The distribution rate constant from the central chamber to the third chamber (unit: ); The distribution rate constant from the second chamber to the central chamber (unit: ); The distribution rate constant from the third chamber to the central chamber (unit: ); Indicates the drug concentration in the second chamber (unit: or ); Indicates the drug concentration in the third compartment (unit: or ); Time (unit: min) is the independent variable of the differential equation.

[0074] The physical meaning of this differential equation is: the rate of change of concentration in the central chamber equals the amount of drug infused per unit time minus the amount of drug eliminated, plus the amount of drug returning from the peripheral chamber minus the amount of drug distributed to the peripheral chamber. Wherein, The term represents the rate of concentration change caused by infusion into the central chamber per unit time; The term represents the rate of concentration decrease caused by elimination from the central chamber and distribution to the peripheral chambers; The term represents the rate of increase in concentration caused by the recirculation from the peripheral chamber to the central chamber.

[0075] (2) Construct the differential equation for the concentration change in the second chamber; The second compartment represents the superficial peripheral tissue, and its concentration changes are determined by drug transport between it and the central compartment. The differential equation for the concentration change in the second compartment is as follows (denoted as Equation 15): ; in, Indicates the drug concentration in the second chamber (unit: or ); The distribution rate constant from the central chamber to the second chamber (unit: ); Indicates the drug concentration in the central chamber (unit: or ); The distribution rate constant from the second chamber to the central chamber (unit: ).

[0076] The physical meaning of this differential equation is: the rate of change of concentration in the second chamber is equal to the amount of drug entering from the central chamber minus the amount of drug returning to the central chamber.

[0077] (3) Construct the differential equation for the concentration change in the third chamber; The third compartment represents the deep peripheral tissues, and its concentration changes are also determined by drug transport between it and the central compartment. The differential equation for the concentration change in the third compartment is as follows (denoted as Equation 16): ; in, Indicates the drug concentration in the third compartment (unit: or ); The distribution rate constant from the central chamber to the third chamber (unit: ); Indicates the drug concentration in the central chamber (unit: or ); The distribution rate constant from the third chamber to the central chamber (unit: ).

[0078] The physical meaning of this differential equation is: the rate of change of concentration in the third chamber is equal to the amount of drug entering from the central chamber minus the amount of drug returning to the central chamber.

[0079] (4) Construct the differential equation for the concentration change in the effect room; The effect chamber is a virtual site of action where a drug produces a pharmacological effect; its concentration change is driven by the difference between the concentration in the central chamber and the concentration in the effect chamber. The differential equation for the concentration change in the effect chamber is as follows (denoted as Equation 17): ; in, Indicates the effect-site concentration of intravenously infused anesthetic drugs (unit: or ), which is the final output variable that needs to be solved in this step; Represents the elimination rate constant of the effect chamber (unit: This parameter reflects the rate at which a drug is eliminated from the effect compartment; it is determined by the type of drug and is a known constant. Indicates the drug concentration in the central chamber (unit: or ); Indicates time (unit: min).

[0080] The physical meaning of this differential equation is: the rate of change of concentration in the effect chamber is proportional to the difference between the concentration in the central chamber and the concentration in the effect chamber, with a proportionality constant of... When the concentration in the central chamber is higher than that in the effect chamber, the concentration in the effect chamber increases; conversely, it decreases.

[0081] (5) Determine the pharmacokinetic parameters of the three-compartment model; The pharmacokinetic parameters of the three-compartment model include , , , , , , These parameters are determined by the type of drug and can be obtained through literature review or clinical trials. Taking propofol as an example, its typical parameter values ​​are as follows: central compartment distribution volume... (Standard adult); Elimination rate constant ; Distribution rate constant from the central chamber to the second chamber ; Distribution rate constant from the central chamber to the third chamber The rate constant of the second chamber to the central chamber distribution The rate constant of the distribution from the third chamber to the central chamber Effect chamber elimination rate constant Different intravenously infused anesthetic drugs have different pharmacokinetic parameters, requiring the selection of appropriate parameter values ​​based on the specific drug. Furthermore, these parameters can be individually adjusted according to factors such as the patient's age, weight, and liver and kidney function to improve the model's predictive accuracy.

[0082] (6) Solve the system of differential equations using numerical integration.

[0083] The above formulas (14), (15), (16), and (17) constitute a system of ordinary differential equations, describing the dynamic distribution process of intravenously infused anesthetic drugs in a three-compartment model. Similar to the five-compartment model, this system of equations can also be solved numerically using the fourth-order Runge-Kutta method to obtain the effect-compartment concentration of the intravenously infused anesthetic drugs in real time. .

[0084] This optional embodiment achieves real-time calculation of the effect-site concentration of intravenously infused anesthetic drugs based on a three-compartment model through the above six calculation steps. This three-compartment model can accurately describe the rapid distribution and slow elimination characteristics of intravenous anesthetic drugs in the body, and outputs the effect-site concentration in real time, synchronized with the drug's efficacy, providing precise intravenous input for the evaluation of combined anesthetic drug efficacy.

[0085] Step 30: Based on the effect-site concentrations of inhaled anesthetic drugs and intravenously infused anesthetic drugs, calculate the combined anesthetic efficacy using a combined pharmacodynamic evaluation model.

[0086] In this embodiment, based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug calculated in steps 10 and 20 respectively, a combined pharmacodynamic evaluation model is specifically introduced to perform nonlinear fusion calculations on the combined administration effect of the inhaled anesthetic drug and the intravenously infused anesthetic drug. The combined pharmacodynamic evaluation model is a mathematical model used to describe the pharmacodynamic interactions (such as synergistic, additive, or antagonistic effects) of two or more drugs used in combination. It integrates the drug effects of different administration routes through a unified pharmacodynamic interface (i.e., effect-site concentration), comprehensively considering the nonlinear interactions between drugs, thereby accurately evaluating the overall anesthetic efficacy under combined anesthesia and overcoming the evaluation bias caused by the traditional linear summation method neglecting drug interactions.

[0087] In this embodiment, the combined pharmacodynamic evaluation model can specifically be a multivariate response surface model, an equivalent concentration or equivalent dose model, a combined pharmacodynamic model based on probability or nonlinear mapping, or a combined effect model based on parametric or nonparametric methods. As long as the model can characterize the nonlinear pharmacodynamic response features of drug combinations at different ratios based on effect-site concentration, it can be understood as falling within the scope of protection of this application. In this embodiment, by converting the effect-site concentrations of inhaled anesthetic drugs and intravenously infused anesthetic drugs into normalized efficacy units, and constructing a combined effect function based on these normalized efficacy units, the combined anesthetic efficacy can be calculated. This combined anesthetic efficacy is a quantitative indicator characterizing the overall depth of anesthesia under combined administration conditions. By introducing drug ratio parameters and model characteristic parameters related to these ratio parameters, the influence of drug interactions on the overall efficacy under different ratios can be accurately reflected, ultimately outputting a quantitative pharmacodynamic value that can be intuitively used for clinical reference.

[0088] Optionally, in some embodiments, the combined efficacy evaluation model adopts an S-shaped concentration-response relationship model.

[0089] In this optional embodiment, the S-shaped concentration-response model (i.e., the Hill equation) is used as the basic framework for the combined drug efficacy evaluation model for illustrative purposes. For details, please refer to [link to relevant documentation]. Figure 4The S-shaped concentration-response model is a classic model in pharmacodynamics describing the relationship between drug concentration and pharmacological effect. It accurately depicts the gradual increase in efficacy as drug concentration increases from low to high, possessing clear pharmacological significance and a broad clinical application basis. This model differs from simple linear additive models; it can accurately describe the pharmacodynamic response characteristics of different drug combinations at various ratios through nonlinear functions, including synergistic, additive, and antagonistic pharmacodynamic interactions. By introducing drug ratio parameters to model the model's characteristic parameters as continuous functions, the model can accurately predict combined efficacy under any drug ratio. This optional embodiment extends the single-drug model into a binary compound drug model by introducing drug ratio parameters to the classic S-shaped concentration-response model, thereby constructing a combined effect model with independent maximum effect, half-maximum effect unit, and curve steepness parameters under any dosage ratio. Its core idea is to regard the combined effect of any two drugs A (inhaled anesthetic) and B (intravenous anesthetic) as a "virtual new drug". Under given proportional parameters, this virtual drug has its corresponding maximum efficacy, the number of units required for a 50% effect, and the steepness of the concentration-effect curve. Based on this, the equivalent minimum alveolar effective concentration value under combined administration conditions can be calculated.

[0090] Optionally, in some embodiments, the combined anesthetic efficacy is calculated using a combined pharmacodynamics evaluation model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug. This includes: calculating the normalized power units (NPUs) of each drug based on the effect-site concentrations of the inhaled and intravenously infused anesthetic drugs; calculating the drug proportioning parameter based on the normalized power units; expressing the combined effect of the inhaled and intravenously infused anesthetic drugs as a function of the normalized total drug units, and introducing the maximum effect, half-effect unit, and curve steepness parameters related to the drug proportioning parameter to construct a combined pharmacodynamics evaluation model; wherein the maximum effect, half-effect unit, and curve steepness parameters are polynomial functions of the drug proportioning parameter, and satisfy the constraint condition that the model degenerates into a single drug effect model when the drug proportioning parameter takes boundary values; and calculating the combined anesthetic efficacy based on the combined pharmacodynamics evaluation model.

[0091] In this optional embodiment, the construction process of the combined drug efficacy evaluation model is described in detail, specifically including the following steps: (1) Calculate the normalized potency units of each drug; Let the effect-site concentration of inhaled anesthetic drug A be... (i.e., the result calculated in step 20 above) The effect-site concentration of intravenously administered anesthetic drug B is... (i.e., the result calculated in step 20 above) The concentrations at which each drug, when administered alone, produces 50% of its maximum efficacy are respectively and The normalized potency units for drug A and drug B are defined as follows (denoted as Formula 18): ; And (denoted as Formula 19): ; in, The normalized potency unit for inhaled anesthetic drug A represents the ratio of the current effect-site concentration of the inhaled anesthetic drug to its 50% maximum potency concentration, and is a dimensionless value. The normalized potency unit for intravenously infused anesthetic drug B represents the ratio of the current effect-site concentration of the intravenously infused anesthetic drug to its 50% maximum potency concentration, and is a dimensionless value. This refers to the effect-site concentration (unit: vol% or mL / dL) required to achieve 50% of the maximum efficacy when inhaled anesthetic drug A is administered alone. This parameter is determined by the type of drug and is a known constant, obtainable through literature review or clinical trials, such as sevoflurane. It is approximately 1.71 vol% (i.e., the lowest effective alveolar concentration), isoflurane is approximately 1.15 vol%, and desflurane is approximately 6.0 vol%. The effect-site concentration (unit: ) corresponding to 50% of the maximum efficacy when anesthetic drug B is administered intravenously alone. or This parameter is also determined by the type of drug and is a known constant, such as propofol. Approximately 3.4 (Used for its sedative-hypnotic effects), remifentanil Approximately 1.98 ng / mL (for analgesic effect). Through normalization, the effect-site concentrations of different drugs and different units are converted into dimensionless normalized potency units, thereby establishing a comparable interface between different drugs. When When, it means that the effect-site concentration of inhaled anesthetic drug A has reached exactly 50% of its maximum effective concentration; when When the concentration of the anesthetic drug B administered intravenously reaches exactly 50% of its maximum effective concentration, it indicates that the effect-site concentration has reached exactly 50% of its maximum effective concentration.

[0092] (2) Calculate the drug ratio parameters; Further define drug ratio parameters As follows (denoted as Formula 20): ; in, This is a drug proportion parameter, a dimensionless value, and its range is... .when When, it means That is, only drug A (pure inhalation anesthesia) exists; when When, it means This indicates the presence of only drug B (pure intravenous infusion anesthesia); values ​​between 0 and 1 represent any mixing ratio of the two drugs. Drug ratio parameter These are key parameters describing the relative contribution ratios of the two drugs in the current dosing combination, and are also parameters for subsequent combined effect models (including...). , and All of them are Parameterize the independent variable. It should be noted that... The value changes in real time with the administration status. When the administration rate of inhaled anesthetic drugs and intravenously infused anesthetic drugs changes, The value of also changes accordingly, thus dynamically reflecting the relative contribution of the two drugs in the current dosing combination.

[0093] (3) Construct a combined drug efficacy evaluation model; Based on the above definition, the combined effect of the two drugs is expressed as a function of the normalized total drug units, and a proportionality-related parameter is introduced to establish the following combined drug effect model (denoted as Equation 21): ; in, The efficacy of combined drug administration is defined as the range of values. ; This represents the baseline effect (i.e., the basic efficacy level before drug administration, usually taken as 0, indicating no anesthetic effect). To the proportional parameter The maximum efficacy under the given conditions represents the theoretically maximum anesthetic effect that can be achieved with the current drug ratio. To the proportional parameter Under certain conditions, the maximum efficacy can be achieved (i.e., and midpoint The required normalized total number of drug units; To the proportional parameter The Hill coefficient (i.e., the steepness parameter of the concentration-response curve) under certain conditions reflects the sensitivity of drug efficacy to changes in drug concentration. The larger the value, the steeper the curve, meaning the drug effect transitions rapidly from low to high within a narrow concentration range; This represents the normalized total number of drug units.

[0094] The physical meaning of this formula is: the combined anesthetic effect is influenced by the baseline effect. It consists of two parts: the effect increment and the concentration-effect increment, where the effect increment follows an S-shaped concentration-effect relationship. hour, (No increase in drug efficacy); when hour, (To achieve maximum efficacy); when hour, (Achieving half-maximal effect). In the molecule The term represents the maximum magnitude of the effect increment, ensuring the efficacy of the drug. and The changes occur continuously between these points.

[0095] The above model maintains the structure of the classic S-shaped concentration-response relationship in form, while using proportional parameters... By introducing drug interaction characteristics, each proportion of drug A and drug B can exhibit its own S-shaped concentration-effect relationship. See details... Figure 4 The schematic diagram of the response surface is shown. The leftmost and rightmost sides of the response surface represent the concentration-effect relationships of drug A and drug B, respectively. The radial lines on the surface show the S-shaped concentration-effect relationships of drug A and drug B at different mixing ratios. The effect of any combination of drug A and B is described by this response surface.

[0096] (4) Perform polynomial parameterization on the proportional-related parameters; To describe the continuous variation characteristics of the combined effect parameters under different drug ratios, we used the following... Polynomial functions to describe respectively , and Its general form is as follows (denoted as Formula 22): ; Among them, the function They can be represented separately , or ; to The coefficients are the corresponding polynomial coefficients, usually provided in the literature or collected from relevant experiments. Using a fourth-order polynomial can avoid overfitting while ensuring model flexibility, and its order can also be adjusted to second, third, or higher orders according to actual fitting needs.

[0097] It should be noted that for the above three proportional parameters, their constant terms... and coefficient of the first term These are not free parameters, but are uniquely determined by the boundary degradation constraints. Specifically, they will... and Substituting each into the general polynomial form, we obtain two expressions related to... and The linear equations can be solved by solving the simultaneous equations. and use , , And boundary value representation, thereby reducing the number of free parameters from 5 to 3 (i.e. , , This reduces the risk of model overfitting.

[0098] (5) Apply boundary degradation constraints; To ensure that the model is consistent with the classical single-drug model when only a single drug is involved, the following boundary constraints are imposed on the polynomial parameters: when (When only drug A is present): ; when (When only drug B is present): ; in, and These represent the maximum efficacy of drug A and drug B when administered alone, respectively. and These are the steepness parameters of the concentration-response curves when drug A and drug B are administered alone.

[0099] By reconstructing the polynomial constant term and the linear term, the model is made to... and This is a single-drug effect model where the drug naturally degenerates into either drug A or drug B. Under the aforementioned boundary conditions, the boundary constraints are substituted into the general polynomial form, and the constant term is... and coefficient of the first term When performing elimination, the proportional-related parameters can be specifically expressed as: Maximum effect function (denoted as Equation 23): ; in, The maximum efficacy of drug A when administered alone (i.e. time value); The maximum efficacy of drug B when administered alone (i.e. time value); , , These are the second, third, and fourth order polynomial coefficients of the maximum effect function, respectively, used to describe the degree to which the maximum effect of the drug combination deviates from linear interpolation at the intermediate proportion. The derivation of the above formula is as follows: Substituting into the general polynomial, we get ;Will Substitution , eliminate simultaneously The coefficient of the linear term is thus obtained as .when hour, Degenerate into and Linear interpolation between them.

[0100] 50% effect unit function (denoted as Equation 24): ; in, , , These are the coefficients of the second, third, and fourth order polynomials for the 50% effect unit function, respectively. Due to boundary constraints... and ,Will Substituting into the general polynomial, we get ;Will Substitution ,Right now Thus ensuring and Place The value is 1. When hour, This indicates that the combined effect of the two drugs in any proportion is simply additive.

[0101] Curve steepness function (denoted as Formula 25): ; in, The steepness parameter of the concentration-response curve when drug A is administered alone (i.e., time value); The steepness parameter of the concentration-response curve when drug B is administered alone (i.e., time value); , , These are the second, third, and fourth order polynomial coefficients of the kurtosis function, respectively. The derivation of the above formulas is similar to that of formula 23: ... Substituting into the general polynomial, we get ;Will Substitution , eliminate simultaneously The coefficient of the linear term is thus obtained as .

[0102] Among the above parameters, second-order and higher polynomial terms (i.e. , (etc.) are used to describe the synergistic, additive, or antagonistic effects between drugs. When the coefficients of second-order and higher terms are zero, the model degenerates into a simple linear interpolation form, corresponding to an additive effect; when .... When the ratio is lower than the linear interpolation at the middle ratio, it indicates a synergistic effect; conversely, it indicates an antagonistic effect.

[0103] (6) Calculate the efficacy of the combined anesthetic.

[0104] In the proportional parameter Under certain conditions, the normalized total drug units at the current moment will be... Substituting into formula 21, the current combined anesthetic effect can be calculated. The efficacy of this combined anesthetic is a dimensionless quantitative indicator that reflects the overall depth of anesthesia under current combined drug administration conditions.

[0105] This optional embodiment achieves the calculation of combined anesthetic efficacy based on the S-shaped concentration-effect relationship model through the above six steps. This model incorporates a drug proportion parameter. The polynomial parameterization method can accurately describe the pharmacodynamic response characteristics of combined administration under any drug ratio. At the same time, the boundary degradation constraint ensures that the model is consistent with the classical single-drug model under single-drug conditions, thereby ensuring the physical rationality and clinical interpretability of the model.

[0106] Optionally, in some embodiments, after calculating the combined anesthetic efficacy using a combined pharmacodynamics assessment model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, the method further includes: calculating the minimum alveolar effective concentration equivalent value based on the combined anesthetic efficacy; and determining the interaction nature between the inhaled anesthetic drug and the intravenously infused anesthetic drug based on the half-response unit parameter of the combined pharmacodynamics assessment model, wherein the interaction nature includes synergistic effects, additive effects, and antagonistic effects.

[0107] In this optional embodiment, after calculating the combined anesthetic effect, two additional derivative calculation functions are provided: (1) Calculate the equivalent value of the lowest effective alveolar concentration; In the proportional parameter Under certain conditions, This represents the normalized number of drug units required to achieve a 50% maximum effect at this ratio; this value is the equivalent minimum alveolar concentration (eMAC) of the combined drug at this ratio. For ease of clinical use, the total unit volume is compared with... The ratio converts the equivalent minimum effective alveolar concentration value into a multiple of the minimum effective alveolar concentration that doctors can intuitively understand the anesthesia status. The calculation formula is as follows (denoted as Formula 26): ; in, This represents the minimum effective alveolar concentration multiple, and is a dimensionless value. This represents the normalized total number of drug units at the current moment. Current drug ratio The number of units of the half-effect.

[0108] The derivation of this formula is as follows: , Substituting into formula 21, we get .when hour, This means achieving 50% of the maximum effect (corresponding to the definition of the minimum effective alveolar concentration: the concentration of anesthetic drug that prevents 50% of patients from producing a somatosensory response to skin incision stimulation). Therefore... This indicates the number of minimum alveolar effective concentrations (MINEFs) equivalent to the current combined anesthetic effect. A result of 1.0 indicates that the current combined anesthetic effect is equivalent to 1.0 MINEF, which is the depth of anesthesia at which 50% of patients do not exhibit a somatomotor response upon skin incision stimulation. A result of 1.3 indicates that the current combined anesthetic effect is equivalent to 1.3 MINEFs, which is the generally recommended depth of surgical anesthesia. By converting the combined anesthetic effect into a multiple of the MINEF familiar to clinicians, doctors can intuitively understand whether the current depth of anesthesia is within a safe range, thus assisting in clinical anesthesia decisions.

[0109] (2) Determine the nature of drug interactions.

[0110] according to The value of can be used to determine the nature of drug interactions. Because Indicates the current drug ratio The normalized total number of drug units required to achieve 50% of the maximum effect, and the normalized potency units. and The definition makes single drugs in At that time, the effect reached exactly 50% of its maximum, therefore The value of directly reflects the interaction properties when two drugs are used in combination. The specific determination rules are as follows: When When the combined use of two drugs results in a synergistic effect, it indicates that, at the current ratio, the normalized total drug units required to achieve a 50% maximum effect are less than the number of units required when each drug is used alone. This means the combined use enhances the efficacy of the drug and is considered a synergistic effect. When the combined effect of drugs equals the sum of the effects of each drug used alone, it is considered an additive effect; when When the combined medication effect is weakened, it is considered an antagonistic effect.

[0111] Optionally, in some embodiments, the interaction nature between the inhaled anesthetic drug and the intravenously infused anesthetic drug is determined based on the half-response unit parameter of the combined pharmacodynamic evaluation model, including: calculating... The deviation between the additive effect reference value and the target value; when the deviation is within the preset tolerance range, it is determined to be an additive effect; when the deviation is less than the negative tolerance threshold, it is determined to be a synergistic effect; when the deviation is greater than the positive tolerance threshold, it is determined to be an antagonistic effect.

[0112] In this optional embodiment, a refined determination method based on deviation is further provided. Because in actual clinical calculations, The value of is affected by factors such as numerical precision and parameter fitting error. Directly using the equivalence criterion may be too strict. Therefore, a tolerance range is introduced for the determination. Specifically, the calculation... Deviation between the summation reference value 1 and the value 1 ,when Within the preset tolerance range (e.g.) or When the sum is within ) it is determined to be additive; when Less than the negative tolerance threshold (e.g.) When ), it is determined to be a synergistic effect; when Greater than the positive tolerance threshold (e.g.) When the value is within a certain range, it is determined to be an antagonistic effect. By introducing a tolerance range, frequent jumps in the determination results caused by numerical fluctuations can be avoided, thereby improving the stability and clinical usability of the determination results.

[0113] The above embodiments and optional embodiments are specifically used to utilize Figure 4 The S-shaped concentration-effect relationship model described in [the text] will be used as an example for illustration. Specific model parameters include: normalized power units. and Drug ratio parameters Baseline effect Maximum effect function and its polynomial coefficients , , Half-number effect unit function and its polynomial coefficients , , , Curve steepness function and its polynomial coefficients , , and boundary degradation constraint parameters , , , Among these parameters, , , , , , These are single-drug pharmacodynamic parameters, determined by the type of drug, and can be obtained through literature review or clinical trials; , , , , , , , , Free parameters describing drug interactions can be obtained by fitting clinical trial data of combined drug use. Using the above parameterization methods, the combined drug efficacy assessment model can accurately predict the efficacy of combined anesthetic drugs under any drug ratio, while boundary degradation constraints ensure that the model is consistent with the classic monotherapy model under single-drug conditions.

[0114] Optionally, in some embodiments, after calculating the combined anesthetic efficacy using a combined pharmacodynamics assessment model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, the method further includes: displaying one or more of the following information via a user interface: combined anesthetic efficacy, minimum alveolar effective concentration equivalent value, and drug interaction properties; and issuing a warning via the user interface when the minimum alveolar effective concentration equivalent value exceeds a preset threshold range.

[0115] In this optional embodiment, a visualization of the evaluation results and a safety warning function are further provided. Specifically, one or more of the following information are displayed in real time through the user interface (UI display module): the combined anesthetic efficacy value (i.e., ), the minimum effective alveolar concentration multiple (i.e. Drug interaction properties (synergistic / additive / antagonistic), effect-site concentrations of each drug, and drug proportion parameters. This information is presented in the form of intuitive numerical values, trend curves, or status indicator lights, enabling clinicians to quickly grasp the current anesthesia status.

[0116] Simultaneously, when the minimum effective alveolar concentration (MPC) exceeds a preset threshold range, a warning is issued via the user interface. For example, a lower threshold (e.g., 0.8) and an upper threshold (e.g., 1.5) can be set for the MPC. When the MPC is below the lower threshold, it indicates insufficient anesthesia, posing a risk of intraoperative awareness; when the MPC is above the upper threshold, it indicates excessive anesthesia, posing a risk of hemodynamic inhibition and delayed awakening. Specific forms of warnings can include audible and visual alarms, interface color changes, and pop-up notifications to promptly draw the attention of clinicians. This warning mechanism allows clinicians to be promptly alerted to adjustments when the depth of anesthesia deviates from the safe range, thereby improving anesthesia safety.

[0117] Optionally, in some embodiments, after calculating the combined anesthetic efficacy using a combined pharmacodynamics assessment model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, the method further includes: storing the combined anesthetic efficacy, the minimum alveolar effective concentration equivalent value, the drug interaction properties, and the corresponding dosing information and effect-site concentration in a time series for postoperative review and quality management.

[0118] In this optional embodiment, data storage and traceability functions are further provided. Specifically, the calculated combined anesthetic efficacy, minimum alveolar effective concentration multiple, drug interaction properties, and corresponding dosing information (including inhaled anesthetic gas concentration, infusion rate, etc.) and effect-site concentrations (including inhalation and intravenous sides) for each sampling period are stored in time series to form a complete anesthetic efficacy record. These records can be used for postoperative retrospective analysis to help evaluate the rationality of the anesthesia plan, and can also be used for quality management and continuous improvement, providing data support for clinical research and teaching. The stored data can also generate time-series trend curves, intuitively displaying the dynamic changes in the depth of anesthesia during surgery, facilitating rapid diagnosis and verification.

[0119] See Figure 5 , Figure 5 This is a schematic diagram of an embodiment of the compound anesthetic efficacy evaluation device provided in this application.

[0120] The combined anesthetic efficacy evaluation device 40 includes: a synchronous real-time data acquisition module 41, used to synchronously acquire inhaled anesthetic drug administration information and intravenous infusion anesthetic drug administration information in real time; an inhaled anesthetic drug effect-site concentration calculation module 42, used to calculate the effect-site concentration of the inhaled anesthetic drug based on the inhaled anesthetic drug administration information and a first drug model; an intravenous infusion anesthetic drug effect-site concentration calculation module 43, used to calculate the effect-site concentration of the intravenous infusion anesthetic drug based on the intravenous infusion anesthetic drug administration information and a second drug model; and a fusion efficacy calculation module 44, used to calculate the combined anesthetic efficacy based on the effect-site concentrations of the inhaled anesthetic drug and the intravenous infusion anesthetic drug using a combined efficacy evaluation model.

[0121] Optionally, in some embodiments, the synchronous real-time data acquisition module 41 is further configured to: acquire drug administration data from the anesthesia machine and infusion pump in real time; standardize the acquired drug administration data to obtain drug administration information for inhaled anesthetic drugs and drug administration information for intravenous infusion anesthetic drugs, and synchronously output the information to the corresponding drug model.

[0122] Optionally, in some embodiments, the compound anesthetic efficacy evaluation device 40 further includes an asynchronous time-sharing calculation module, which is used to: divide the single inhalation anesthetic effect room concentration update process into multiple independently schedulable calculation stages; execute each calculation stage sequentially in different scheduling cycles according to a preset scheduling order, and maintain intermediate calculation results between scheduling cycles to achieve continuous progress across cycles; when all multiple calculation stages are completed, perform physical feasibility constraints and boundary limit processing on the calculation results to obtain the effect room concentration of the inhalation anesthetic drug.

[0123] Optionally, in some embodiments, the asynchronous time-sharing calculation module includes: a task initiation unit, used to generate a new round of inhalation anesthesia concentration update task after receiving the synchronous input data of the current cycle, and save the input parameters, time information and initial state required for the round of task; a stage scheduling unit, used to divide the entire round of inhalation anesthesia effect room concentration calculation task into multiple calculation stages according to a preset scheduling order, and execute them sequentially at different scheduling times; an intermediate result holding unit, used to hold the intermediate state, intermediate derivatives, temporary calculation results and stage progress information of the current round of task between each scheduling cycle; and a result submission unit, used to perform unified inspection and post-processing on the state results obtained in this round of update after all stages are completed, including performing physical feasibility constraints, boundary restrictions, state write-back and derivative quantity updates, and outputting the finally obtained inhalation anesthesia effect room concentration to the subsequent fusion pharmacodynamics calculation module.

[0124] Optionally, in some embodiments, the inhaled anesthetic effect-site concentration calculation module 42 and the intravenous infusion anesthetic effect-site concentration calculation module 43 are further configured to: obtain patient basic information before calculating the effect-site concentration, the patient basic information including one or more of height, weight, age, and gender; and based on the patient basic information, perform individualized adjustments to the model parameters of the first drug model and the model parameters of the second drug model.

[0125] Optionally, in some embodiments, both the first drug model and the second drug model employ a multi-compartment pharmacokinetic model; the first drug model includes alveolar compartments, multiple tissue compartments, and an effect compartment to simulate the distribution process of inhaled anesthetic drugs in the body; the second drug model includes a central compartment, at least one peripheral compartment, and an effect compartment to simulate the distribution process of intravenously infused anesthetic drugs in the body.

[0126] Optionally, in some embodiments, the first drug model is a five-compartment model, which includes an alveolar compartment, a highly vascularized tissue compartment, a muscle tissue compartment, an adipose tissue compartment, an anemic flow tissue compartment, and a first virtual effect compartment.

[0127] Optionally, in some embodiments, the second drug model is a three-compartment model, which includes a central compartment, a second compartment, a third compartment, and a second virtual effect compartment.

[0128] Optionally, in some embodiments, the combined efficacy evaluation model adopts an S-shaped concentration-response relationship model.

[0129] Optionally, in some embodiments, the fusion pharmacodynamics calculation module 44 is further configured to: calculate the normalized efficacy units of each drug based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug; calculate the drug proportioning parameter based on the normalized efficacy units; express the combined effect of the inhaled anesthetic drug and the intravenously infused anesthetic drug as a function of the normalized total drug units, and introduce the maximum effect, half-effect unit parameters, and curve steepness parameters related to the drug proportioning parameter to construct a combined pharmacodynamics evaluation model; wherein the maximum effect, half-effect unit parameters, and curve steepness parameters are polynomial functions of the drug proportioning parameter, and satisfy the constraint condition that the model degenerates into a single drug effect model when the drug proportioning parameter takes boundary values; and calculate the combined anesthetic efficacy based on the combined pharmacodynamics evaluation model.

[0130] Optionally, in some embodiments, the fusion pharmacodynamics calculation module 44 is further configured to: calculate the minimum alveolar effective concentration equivalent value based on the combined anesthetic pharmacodynamics; and determine the interaction properties between the inhaled anesthetic drug and the intravenously infused anesthetic drug based on the half-response unit parameter of the combined pharmacodynamics evaluation model, wherein the interaction properties include synergistic effects, additive effects, and antagonistic effects.

[0131] Optionally, in some embodiments, the fusion efficacy calculation module 44 is further used to: calculate The deviation between the additive effect reference value and the target value; when the deviation is within the preset tolerance range, it is determined to be an additive effect; when the deviation is less than the negative tolerance threshold, it is determined to be a synergistic effect; when the deviation is greater than the positive tolerance threshold, it is determined to be an antagonistic effect.

[0132] Optionally, in some embodiments, the combined anesthetic efficacy evaluation device 40 further includes an interface display module, used to: display one or more information such as combined anesthetic efficacy, minimum alveolar effective concentration equivalent value, and drug interaction properties through the user interface; and issue a warning prompt through the user interface when the minimum alveolar effective concentration equivalent value exceeds a preset threshold range.

[0133] Optionally, in some embodiments, the combined anesthetic efficacy evaluation device 40 further includes a data storage module for storing the combined anesthetic efficacy, the minimum alveolar effective concentration equivalent value, the drug interaction properties, and the corresponding dosing information and effect-site concentration in a time series for postoperative review and quality management.

[0134] Based on the above structure, the combined anesthetic efficacy evaluation device 40 of this application forms the following collaborative relationship among the synchronous real-time data acquisition module 41, the inhaled anesthetic effect-room concentration calculation module 42, the intravenous infusion anesthetic effect-room concentration calculation module 43, and the fusion efficacy calculation module 44: The synchronous real-time data acquisition module 41 is responsible for forming the input snapshot of the current period within a unified sampling period; the inhaled anesthetic effect-room concentration calculation module 42 and the intravenous infusion anesthetic effect-room concentration calculation module 43 respectively read the corresponding input snapshot; the inhaled anesthetic effect-room concentration calculation module 42 performs cross-period scheduling of the highly complex calculation process on the inhalation side through asynchronous time-sharing calculation; when the time-sharing calculation on the inhalation side is completed in this round, the updated inhaled effect-room concentration is written into the shared result area; the fusion efficacy calculation module reads the most recent valid inhaled effect-room concentration and intravenous effect-room concentration from 44, calculates the current combined anesthetic efficacy value and outputs it, which can be used by the interface display module for visualization and early warning judgment, and can also be used by the data storage module for data recording. This collaborative approach enables a "real-time data acquisition, time-sharing computation, and continuous result updates" operational behavior. It ensures input data comes from the latest equipment while avoiding the concentrated consumption of controller computing resources by highly complex models, thus achieving a clinical decision support function that balances automation, real-time performance, safety, and traceability. This device can be a standalone medical device, a functional module integrated into existing anesthesia equipment, or a main control platform or independent processing unit of an anesthesia machine deploying a system capable of implementing the aforementioned combined anesthetic efficacy assessment method. As long as it can achieve the aforementioned collaborative processing logic of synchronous real-time data acquisition and asynchronous time-sharing computation to complete the real-time assessment of combined anesthetic efficacy, it can be understood to fall within the protection scope of the embodiments of this application.

[0135] Since the embodiments of the device part correspond to the embodiments of the above method, the description of the compound anesthetic efficacy evaluation device 40 provided in this application embodiment should refer to the above method embodiment. The embodiments of this application will not be repeated here, but it has the same beneficial effects as the above compound anesthetic efficacy evaluation method.

[0136] See Figure 6 , Figure 6 This is a schematic diagram of an embodiment of the storage medium provided in this application.

[0137] The storage medium 50 stores program data 51, which, when executed by the processor, implements, as follows: Figures 1 to 4 The method for evaluating the efficacy of combined anesthetic drugs described.

[0138] The program data 51 is stored in a storage medium 50 and includes several instructions for causing a network device (such as a router, personal computer, or server) or processor to execute all or part of the steps of the methods of the various embodiments of this application.

[0139] Optionally, the storage medium 50 can be any medium capable of storing program data 51, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), disk, or optical disc.

[0140] See Figure 7 , Figure 7 This is a schematic diagram of the structure of one embodiment of the medical device provided in this application.

[0141] The medical device 60 includes a processor 62 and a memory 61 interconnected. The memory 61 stores a computer program, and when the processor 62 executes the computer program, it implements, for example... Figures 1 to 4 The described method for evaluating the efficacy of combined anesthetic drugs. The memory 61 may include the storage medium 50, or it may be another separately developed memory.

[0142] In this embodiment, the medical device 60 may specifically be an anesthesia workstation, anesthesia machine, intensive care monitor, or operating room central control equipment, etc., and may be equipped with such as Figure 5The described combined anesthetic efficacy evaluation device executes a combined anesthetic efficacy evaluation method directly executed or dispatched by a processor, thereby achieving real-time calculation and evaluation of the combined efficacy of inhaled and intravenously infused anesthetic drugs. Simultaneously, the medical device 60 can optionally be equipped with a combined anesthetic drug delivery device, such as an anesthesia machine for precise control and concentration acquisition of inhaled anesthetic drugs, an infusion pump for precise control and rate acquisition of intravenously infused anesthetic drugs, a carbon dioxide monitoring module for real-time monitoring of alveolar ventilation and functional residual capacity, a blood oxygen monitoring module for real-time monitoring of cardiac output, and other physiological parameter monitoring modules. Any device capable of acquiring drug delivery information for both inhaled and intravenously infused anesthetic drugs and possessing sufficient computational power to execute the aforementioned combined anesthetic efficacy evaluation method can be understood as the medical device 60 protected by this application. This medical device 60 can assess the efficacy of combined anesthetic drugs in real time and accurately during surgery, convert the assessment results into the minimum effective alveolar concentration multiple familiar to clinicians for intuitive display, and issue timely warnings when the depth of anesthesia exceeds the safe range. At the same time, it records complete anesthetic efficacy data for postoperative review and quality management, thereby achieving clinical auxiliary decision-making functions that take into account automation, real-time performance, safety and traceability.

[0143] Unlike existing technologies, this application discloses a method, apparatus, storage medium, and medical device for evaluating the efficacy of combined anesthetic drugs. It simultaneously acquires real-time dosing information for inhaled and intravenously infused anesthetic drugs, calculates their respective effect-site concentrations using a first drug model and a second drug model, and finally calculates the combined anesthetic efficacy based on these two effect-site concentrations using a combined pharmacodynamic evaluation model. The simultaneous real-time acquisition of dosing information ensures that the dosing data from the two heterogeneous dosing pathways remain consistent in time, providing a time-aligned data foundation for subsequent pharmacodynamic fusion calculations. Calculating the effect-site concentrations using the first and second drug models respectively transforms the original dosing information from different routes into a unified pharmacokinetic index representing the actual concentration of the drug at the site of action, thus establishing a comparable interface between drugs administered via different routes. Calculating the combined anesthetic efficacy based on the effect-site concentration using the combined pharmacodynamic evaluation model allows the model to characterize the pharmacodynamic interaction between inhaled and intravenously infused anesthetic drugs, avoiding the problem of excessive evaluation bias caused by neglecting drug interactions when using a simple linear summation method. Through the above methods, this application achieves real-time quantitative assessment of the efficacy of combined anesthetic drugs, improves the accuracy of the assessment, and helps to provide a reliable quantitative reference for clinical anesthesia decision-making.

[0144] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments, storage medium, and medical device embodiments are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0145] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for evaluating the efficacy of compound anesthetic drugs, characterized in that, include: Simultaneously and in real-time acquire information on the administration of inhaled anesthetic drugs and the administration of intravenously infused anesthetic drugs; The effect-site concentration of the inhaled anesthetic drug is calculated based on the drug administration information and the first drug model, and the effect-site concentration of the intravenously infused anesthetic drug is calculated based on the drug administration information and the second drug model. Based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, a combined pharmacodynamic evaluation model is used to calculate the combined anesthetic efficacy.

2. The method for evaluating the efficacy of combined anesthetic drugs according to claim 1, characterized in that, The synchronous real-time acquisition of administration information for inhaled anesthetic drugs and intravenous infusion anesthetic drugs includes: Real-time acquisition of drug administration data from the anesthesia machine and infusion pump; The collected drug administration data is standardized to obtain the drug administration information of the inhaled anesthetic drug and the drug administration information of the intravenous infusion anesthetic drug, and is simultaneously output to the corresponding drug model.

3. The method for evaluating the efficacy of combined anesthetic drugs according to claim 1, characterized in that, The calculation of the effect-site concentration of the inhaled anesthetic drug based on the drug administration information and the first drug model includes: The concentration update process of a single inhalation anesthesia effect room is broken down into multiple independently schedulable computational phases; According to the preset scheduling order, each of the aforementioned calculation stages is executed sequentially within different scheduling cycles, and intermediate calculation results are maintained between scheduling cycles to achieve continuous progress across cycles; After all the calculation stages are completed, the calculation results are subjected to physical feasibility constraints and boundary restrictions to obtain the effect-site concentration of the inhaled anesthetic drug.

4. The method for evaluating the efficacy of combined anesthetic drugs according to claim 1, characterized in that, Before calculating the effect-site concentration of the inhaled anesthetic drug based on the administration information of the inhaled anesthetic drug and the first drug model, and before calculating the effect-site concentration of the intravenously infused anesthetic drug based on the administration information of the intravenously infused anesthetic drug and the second drug model, the method further includes: Obtain basic patient information; the basic patient information includes one or more of the following: height, weight, age, and gender. Based on the patient's basic information, the model parameters of the first drug model and the second drug model are individually adjusted.

5. The method for evaluating the efficacy of combined anesthetic drugs according to claim 1, characterized in that, Both the first drug model and the second drug model employ multi-compartment pharmacokinetic models. The first drug model includes alveolar compartments, multiple tissue compartments, and an effect compartment to simulate the distribution process of inhaled anesthetic drugs in the body. The second drug model includes a central compartment, at least one peripheral compartment, and an effect compartment to simulate the distribution process of intravenously infused anesthetic drugs in the body.

6. The method for evaluating the efficacy of combined anesthetic drugs according to claim 1, characterized in that, The combined anesthetic efficacy is calculated using a combined pharmacodynamic evaluation model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, including: Based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, the normalized potency units of each drug are calculated respectively. Calculate the drug proportion parameters based on the normalized potency units; The combined effect of the inhaled anesthetic and the intravenously infused anesthetic is expressed as a function of the normalized total drug units. A combined pharmacodynamic evaluation model is constructed by introducing the maximum effect, half-effect unit, and curve steepness parameters related to the drug proportion parameter. The maximum effect, half-effect unit, and curve steepness parameters are polynomial functions of the drug proportion parameter, and satisfy the constraint that the model degenerates into a single-drug effect model when the drug proportion parameter reaches its boundary values. The combined anesthetic efficacy is calculated based on the combined pharmacodynamic evaluation model.

7. The method for evaluating the efficacy of combined anesthetic drugs according to claim 1, characterized in that, After calculating the combined anesthetic efficacy using a combined pharmacodynamic evaluation model based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug, the method further includes: Calculate the minimum effective alveolar concentration equivalent value based on the efficacy of the compound anesthetic drug; Based on the half-response unit parameter of the combined pharmacodynamic evaluation model, the interaction properties between the inhaled anesthetic drug and the intravenously infused anesthetic drug are determined, including synergistic, additive, and antagonistic effects.

8. A device for evaluating the efficacy of compound anesthetic drugs, characterized in that, include: The synchronous real-time data acquisition module is used to synchronously and in real-time acquire the administration information of inhaled anesthetic drugs and the administration information of intravenously infused anesthetic drugs; An inhaled anesthetic drug effect-site concentration calculation module is used to calculate the effect-site concentration of the inhaled anesthetic drug based on the drug administration information and a first drug model; The module for calculating the effect-site concentration of intravenously infused anesthetic drugs is used to calculate the effect-site concentration of the intravenously infused anesthetic drugs based on the drug administration information and a second drug model. The integrated pharmacodynamics calculation module is used to calculate the combined anesthetic efficacy based on the effect-site concentrations of the inhaled anesthetic drug and the intravenously infused anesthetic drug using a combined pharmacodynamics evaluation model.

9. A storage medium storing program data thereon, characterized in that, When the program data is executed by the processor, it implements the steps of the combined anesthetic efficacy evaluation method as described in any one of claims 1 to 7.

10. A medical device, characterized in that, It includes an interconnected processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method for evaluating the efficacy of combined anesthetic drugs as described in any one of claims 1 to 7.

Images