Digestive tract tumor operation anesthesia plan making method and system

Abstract

The invention relates to the field of anesthesia effect evaluation, in particular to a digestive tract tumor surgery anesthesia plan making method and system, and the method comprises the following steps: obtaining body surface temperature data of a plurality of monitoring points distributed along a specific region of a patient trunk; acquiring real-time trunk posture information of the patient; establishing an individualized body surface temperature baseline related to epidural anesthesia; based on the body surface temperature data, the individualized body surface temperature base line, the real-time trunk posture information and a preset association rule of a body position and an epidural liquid medicine diffusion trend, an actual retardation plane of epidural anesthesia is evaluated, and the actual retardation plane and a deviation risk are obtained; by obtaining the body surface temperature data and the trunk posture information and combining the individualized baseline and the association rule, the actual retardation plane is dynamically evaluated and the migration risk is predicted, and the problems that in the prior art, it is difficult to dynamically and accurately evaluate the actual retardation plane of epidural anesthesia and predict the migration risk under the influence of the body position are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of anesthetic effect evaluation, and more particularly to a method and system for developing anesthesia plans for gastrointestinal tumor surgery. Background Technology

[0002] In complex gastrointestinal tumor surgeries, general anesthesia combined with epidural anesthesia is often used to provide good intraoperative analgesia and promote postoperative recovery. However, for the needs of the surgical procedure, patients often need to adjust their position during surgery, such as adopting a head-down, feet-up, or lateral decubitus position. These changes in position, due to gravity and subtle changes in the anatomical morphology of the spine and epidural space, can significantly affect the distribution of local anesthetic injected into the epidural space. This may cause the diffusion direction and range of the drug in the epidural space to deviate from the expected direction, resulting in fluctuations in the anesthetic block level. If the block level is too high, it may affect the patient's respiratory and circulatory functions; if the block level is insufficient, adequate analgesia cannot be provided, increasing the patient's physiological stress.

[0003] Existing methods for assessing anesthetic efficacy, such as monitoring physiological indicators like heart rate and blood pressure, are indirect. These indicators are easily affected by various factors, including surgical stimulation, depth of general anesthesia, and blood volume, making it difficult to accurately and promptly reflect the actual distribution of epidural medication and the resulting nerve block level. Especially with dynamic changes in intraoperative positioning, anesthesiologists struggle to accurately grasp the real-time effect of epidural anesthesia, resulting in judgments that are delayed and uncertain. When adjustments to the epidural administration regimen are needed based on anesthetic efficacy, the lack of direct information on the actual distribution of the medication means that adjustment decisions often rely on experience, potentially leading to inaccurate outcomes or even increased risk of side effects. Therefore, overcoming the limitations of existing assessment methods to achieve dynamic and accurate assessment of the actual epidural block level, and to proactively predict the risk of block level shift due to continuous changes in position during surgery, thereby assisting anesthesiologists in more precise anesthetic management, is a significant technical challenge currently facing clinical practice.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method and system for developing anesthesia plans for gastrointestinal tumor surgeries.

[0006] In a first aspect, the present invention provides a method for developing anesthesia plans for gastrointestinal tumor surgery, the method comprising the following steps: Acquire body surface temperature data from multiple monitoring points distributed along a specific region of the patient's torso; Obtain the patient's real-time trunk posture information; Establish an individualized baseline for body surface temperature associated with epidural anesthesia; Based on the body surface temperature data, the individualized body surface temperature baseline, the real-time trunk posture information, and the preset correlation rules between body position and epidural drug diffusion trend, the actual blockade plane of epidural anesthesia is evaluated, and the risk of deviation of the blockade plane due to the continuous influence of body position is predicted, thus obtaining the actual blockade plane and the risk of deviation. Output the actual blocking plane and the offset risk.

[0007] The core innovation of this application lies in combining body surface temperature data reflecting actual physiological effects with real-time trunk posture information characterizing influencing factors, and conducting comprehensive analysis based on preset body position and drug diffusion correlation rules. This enables dynamic assessment of the actual blockade plane of epidural anesthesia and prospective prediction of the risk of blockade plane deviation due to continuous body position influence, thus overcoming the limitations of traditional assessment methods and improving the accuracy of anesthesia management.

[0008] Secondly, a gastrointestinal tumor surgery anesthesia planning system is provided, the system comprising: The temperature data acquisition module is used to acquire surface temperature data from multiple monitoring points distributed along a specific area of ​​the patient's torso; The posture information acquisition module is used to acquire the patient's real-time trunk posture information; The baseline establishment module is used to establish an individualized body surface temperature baseline associated with epidural anesthesia. The block plane assessment and risk prediction module is used to assess the actual block plane of epidural anesthesia based on the body surface temperature data, the individualized body surface temperature baseline, the real-time trunk posture information, and the preset association rules between body position and epidural drug diffusion trend, and to predict the risk of the block plane shift due to the continuous influence of body position, so as to obtain the actual block plane and the shift risk. The result output module is used to output the actual blocking plane and the offset risk.

[0009] Compared with the prior art, the present invention has the following beneficial effects: By acquiring body surface temperature data and trunk posture information, and combining them with individualized baselines and correlation rules, the actual block plane is dynamically assessed and the risk of deviation is predicted. This effectively solves the problem in existing technologies that it is difficult to dynamically and accurately assess the actual block plane of epidural anesthesia and predict the risk of deviation under the influence of body position. It has the advantages of being able to dynamically and accurately assess the actual block plane of epidural anesthesia and prospectively predict the risk of deviation of the block plane due to the continuous influence of body position, thereby assisting anesthesiologists in making more precise anesthesia management. Attached Figure Description

[0010] Figure 1This is a flowchart of the method of the present invention.

[0011] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0012] In the diagram: 201, Temperature Data Acquisition Module; 202, Attitude Information Acquisition Module; 203, Baseline Establishment Module; 204, Stasis Plane Assessment and Risk Prediction Module; 205, Result Output Module. Detailed Implementation

[0013] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0014] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0015] Traditional methods for treating gastrointestinal tumor patients undergoing surgery under a combination of general and epidural anesthesia, especially when significant or prolonged positional changes (such as head-down, feet-up, or lateral decubitus positions) are unavoidable during surgery, present challenges. These include the uncertainty of drug distribution within the epidural space due to gravity, limitations of existing indirect physiological indicators for monitoring the anesthetic plane, and the high precision required for anesthesia management due to the physiological vulnerability of the patient population. These issues make it difficult to accurately assess and predict the effectiveness of epidural anesthesia and introduce the risk of blockade plane deviation, thus compromising anesthetic efficacy and patient safety. Anesthesiologists rely primarily on indirect physiological indicators such as heart rate and blood pressure to assess epidural analgesia during surgery. These indicators are easily affected by surgical stimulation, depth of general anesthesia, blood volume, and other factors, making it difficult to accurately and promptly identify problems caused by abnormal epidural drug distribution, resulting in judgments that are delayed and uncertain. When adjustments to the epidural administration regimen are needed, the lack of direct information on the actual drug distribution means that adjustments are often based on experience, which may not be accurate on the first attempt and could even increase the risk of side effects.

[0016] Therefore, the present application as follows Figure 1 The method shown is a procedure for developing anesthesia for gastrointestinal tumor surgery, which includes the following steps: S101. Obtain surface temperature data from multiple monitoring points distributed along a specific region of the patient's torso; S102. Obtain the patient's real-time trunk posture information; S103. Establish an individualized baseline for body surface temperature related to epidural anesthesia; S104. Based on body surface temperature data, individualized body surface temperature baseline, real-time trunk posture information, and preset association rules between body position and epidural drug diffusion trend, assess the actual blockade plane of epidural anesthesia and predict the risk of deviation of the blockade plane due to the continuous influence of body position, and obtain the actual blockade plane and the risk of deviation. S105, Output the actual blocking plane and offset risk.

[0017] Among them, the individualized body surface temperature baseline refers to the patient-specific reference temperature distribution pattern formed by the body surface temperatures of multiple monitoring points distributed along a specific area of ​​the patient's trunk before the epidural anesthesia effect significantly affects the body surface temperature. It can be achieved by taking multiple measurements and calculating the average value before anesthesia or before the drug effect stabilizes in the early stage of anesthesia, or by establishing a time series model. Its main purpose is to eliminate the influence of individual physiological differences and environmental factors on body surface temperature, so as to more accurately identify temperature changes caused by nerve block. The association rule between body position and epidural drug diffusion trend refers to a set of rules or models that are established in advance to describe the relationship between the patient's trunk posture (such as supine, lateral, head-down, feet-up, etc.) and the diffusion direction and range of local anesthetic drug in the epidural cavity. It can be established based on clinical research data, anatomical models or pharmacokinetic simulations. Its main purpose is to provide a predictive framework for estimating the expected distribution pattern of the drug in a specific body position.

[0018] This application's approach acquires surface temperature data from multiple monitoring points distributed along a specific region of the patient's torso. This data directly reflects the impact of nerve block on local blood flow and temperature. Simultaneously, it acquires real-time torso posture information to identify key external factors affecting drug distribution. After establishing an individualized surface temperature baseline, real-time surface temperature data is compared to the baseline to quantify temperature changes induced by anesthesia. Based on this, and combining real-time torso posture information with pre-defined association rules between body position and epidural drug diffusion trends, the actual block plane reflected by the surface temperature data is evaluated. Posture information and association rules are used to predict potential shifts in drug distribution due to continuous changes in body position. This comprehensive analysis considers the physiological manifestations of drug efficacy, external factors affecting the physical distribution of the drug, and individual physiological factors, thus providing a dynamic and comprehensive assessment of anesthetic efficacy and risk prediction. Finally, the assessed actual block plane and predicted shift risks are output to provide a basis for clinical decision-making.

[0019] As one embodiment of the present invention, the steps of assessing the actual blockade plane of epidural anesthesia and predicting the risk of deviation of the blockade plane due to the continuous influence of body position, based on body surface temperature data, individualized body surface temperature baseline, real-time trunk posture information, and preset correlation rules between body position and epidural drug diffusion trend, and obtaining the actual blockade plane and the risk of deviation, include: Obtain the expected dynamic changes of the blockade plane based on real-time trunk posture information and the association rules between the currently effective preset body position and the diffusion trend of epidural fluid. To obtain the dynamic changes of the actual blockade plane determined based on body surface temperature data and an individualized body surface temperature baseline; The dynamic changes of the actual hindrance plane are compared with the expected dynamic changes of the hindrance plane to determine the differences between the two. If the difference meets the adjustment triggering condition, the drug diffusion characteristic parameter corresponding to the current real-time torso posture information in the difference adjustment association rule is used to form an updated association rule. By employing updated association rules and combining body surface temperature data, individualized body surface temperature baselines, and real-time trunk posture information, the actual blockade plane of epidural anesthesia is assessed, and the risk of deviation of the blockade plane due to the continuous influence of body position is predicted, thus obtaining the actual blockade plane and the risk of deviation.

[0020] Among them, the preset association rules between body position and epidural drug diffusion trend refer to a set of rules established based on clinical experience, pharmacological principles or historical data, which describe the influence of different trunk postures (such as supine, lateral, head-down, feet-up) on the direction, speed and range of drug diffusion in the epidural cavity. It can be implemented by lookup table, mathematical model, expert system or machine learning model, and its purpose is to provide an initial, position-based basis for predicting drug diffusion behavior.

[0021] Among them, the expected dynamic change of the block plane refers to the trend or trajectory of the epidural anesthesia block plane as time or body position changes, which is predicted based on the current real-time trunk posture information and the currently effective association rules. It can be realized by rule-based deduction, dynamic model simulation or prediction algorithm. Its purpose is to provide a theoretical reference for the change of the block plane based on preset rules.

[0022] The dynamic change of the actual blockade plane refers to the real trend or trajectory of the epidural anesthesia blockade plane as a function of time or body position, which is calculated by comparing and analyzing real-time acquired body surface temperature data with individualized body surface temperature baselines. It can be realized by temperature gradient analysis, machine learning regression models or physiological model inversion, and its purpose is to reflect the patient's real drug efficacy response and changes in the blockade plane.

[0023] Among them, the adjustment trigger condition refers to the threshold or standard used to determine whether the difference between the actual dynamic change of the hindrance plane and the expected dynamic change of the hindrance plane reaches the threshold that requires adjustment of the association rule. It can be implemented by fixed threshold, dynamic threshold, statistical significance test or anomaly detection based on machine learning. Its purpose is to ensure that the association rule is adjusted only when necessary, and to avoid excessive or unnecessary correction.

[0024] Among them, the drug diffusion characteristic parameters refer to the key parameters used to quantify the diffusion behavior of the drug in a specific body position in the association rules between body position and epidural drug diffusion trend. These parameters include diffusion rate coefficient, gravity influence factor, and drug distribution bias coefficient. They can be represented in numerical, vector, or functional form. The purpose is to change the prediction results of the association rules on the drug diffusion trend by adjusting these parameters.

[0025] The updated association rule refers to a new association rule formed when the difference between the actual dynamic change of the blockade plane and the expected dynamic change of the blockade plane meets the adjustment trigger condition. The drug diffusion characteristic parameters in the original association rule are corrected based on the difference. It can be implemented by parameter update algorithm (such as gradient descent), rule correction logic or model retraining. Its purpose is to make the association rule more consistent with the patient's current actual drug efficacy response and body position influence, and improve the accuracy of subsequent assessment and prediction.

[0026] This application's solution establishes a dynamic feedback mechanism to continuously optimize the association rules used to assess the efficacy of epidural anesthesia. First, the system uses the patient's current real-time trunk posture information and the association rules between the current effective position and the diffusion trend of the epidural drug to calculate a theoretically expected dynamic change in the blockade plane. This expected change is based on pre-defined knowledge predicting the diffusion trend of the drug in the current position. Simultaneously, the system continuously acquires surface temperature data from multiple monitoring points distributed along specific areas of the patient's trunk and, combined with the patient's individualized surface temperature baseline, calculates the current actual blockade plane and its actual dynamic change over time. Changes in surface temperature are related to vasodilation caused by nerve block and are an objective indicator for assessing the blockade plane. Next, the system compares the dynamic change of the actual blockade plane determined by the surface temperature data with the expected dynamic change of the blockade plane calculated based on the pre-defined rules, quantifying the difference between the two. This difference reflects the degree of deviation of the currently effective association rules in predicting the patient's actual drug response. If the discrepancy found during the comparison meets the preset adjustment trigger conditions, indicating a significant deviation between the current rule's prediction and the actual situation, the system will adjust the drug diffusion characteristic parameters in the association rule corresponding to the current real-time trunk posture information based on this discrepancy. The purpose of the adjustment is to reduce the deviation between the rule prediction and actual observation, making the rule more consistent with the patient's current physiological state and drug response. The adjusted rule then forms an updated association rule. Finally, the system uses this updated association rule, combined with the latest body surface temperature data, individualized body surface temperature baseline, and real-time trunk posture information, to reassess the actual epidural anesthesia blockade plane and predict the risk of the blockade plane shifting due to the continuous influence of body position. By using updated rules calibrated with actual data, the assessment results and predicted risks can more accurately reflect the patient's true condition. This process is continuous, allowing the association rule to adaptively adjust in real-time or near real-time based on the dynamic changes in the patient's intraoperative body position and the actual drug response. This overcomes the limitations of relying solely on static preset rules and improves the accuracy of assessment and prediction. Combined with the basic assessment framework, this dynamic adjustment mechanism enables the entire assessment system to better adapt to individual patient differences and intraoperative complexities, thereby providing more reliable information on anesthetic efficacy and assisting anesthesiologists in making more precise decisions.

[0027] As one embodiment of the present invention, the step of predicting the risk of displacement of the blocking plane due to the continuous influence of body position includes: Acquire pharmacodynamic status information that characterizes the current efficacy status of intradural drug solutions. The pharmacodynamic status information is determined based on physiological processes or human intervention events that affect the properties of the drug solutions. Based on the drug efficacy status information, at least one operational parameter related to the drug diffusion behavior or effect intensity in the prediction calculation process for the risk of displacement of the blocking plane due to the continuous influence of body position is adjusted to obtain the adjusted operational parameter. Based on the adjusted calculation parameters, the risk of displacement of the blocking plane due to the continuous influence of body position is predicted and calculated, and the displacement risk corresponding to the current efficacy state of the drug solution is obtained.

[0028] Among these, pharmacodynamic status information refers to information characterizing the current effective concentration, activity, or potency of local anesthetics within the epidural space. Specifically, this can be determined by monitoring or calculating the pharmacokinetic and pharmacodynamic status of the drug solution within the epidural space, aiming to quantify the actual efficacy level of the drug solution at a specific moment. Physiological processes affecting drug solution characteristics can include the patient's metabolic rate, fluid circulation status, and epidural absorption rate. Human intervention events can include additional drug doses, mixing different drug solutions, and changes in infusion rate; all of these factors can alter the actual efficacy of the drug solution. Operational parameters refer to the variables in the mathematical model or algorithm used to predict drug diffusion behavior or potency. These can include, but are not limited to, the drug diffusion coefficient, drug efficacy decay rate, drug-tissue binding rate, and drug action threshold. The purpose is to adjust these parameters so that the prediction model can more accurately reflect the actual performance of the drug solution under its current potency state.

[0029] This application's solution acquires pharmacodynamic status information characterizing the current efficacy of the drug solution within the epidural space and dynamically adjusts the computational parameters used for prediction calculations based on this information. This allows the predicted risk of blockade plane shift to reflect the actual efficacy changes of the drug solution. Because the diffusion behavior and intensity of the drug solution are not constant but are influenced by various physiological and human factors, predictions based solely on body position changes have limitations. By incorporating pharmacodynamic status information and adjusting relevant parameters in the prediction model accordingly, the prediction process can more closely approximate the actual dynamics of the drug solution within the epidural space. For example, when pharmacodynamic status information indicates a decrease in drug efficacy, the corresponding diffusion rate or intensity parameters are adjusted, ensuring that the predicted shift risk reflects the impact of weakened efficacy on the stability of the blockade plane. This dynamic parameter adjustment based on the actual efficacy status of the drug solution, combined with the previous approach of adjusting association rules based on the difference between the actual and expected dynamic changes of the blockade plane, works together in the prediction process. Previous methods corrected the correlation between body position and diffusion trends by monitoring changes in the retardation plane reflected by actual body surface temperature. This new method, however, starts from the pharmacological state of the drug solution itself, adjusting parameters in the prediction model related to the inherent properties of the drug solution. The two methods complement each other: the former adjusts based on feedback, while the latter adjusts based on causal analysis. This allows for a more comprehensive and accurate capture of multiple factors influencing retardation plane shifts, significantly improving the accuracy and reliability of predictions.

[0030] As one embodiment of the present invention, the steps of obtaining pharmacodynamic status information characterizing the current efficacy status of the epidural fluid, wherein the pharmacodynamic status information is determined based on physiological processes or human intervention events affecting the properties of the fluid, include: Obtain event parameters for each epidural medication administration operation, including administration time, medication type, and dosage for each operation. For each epidural drug administration operation, the efficacy characteristics parameters corresponding to the type of drug administered in that operation are obtained. These efficacy characteristics parameters characterize the efficacy behavior of that type of drug. For each epidural drug administration procedure, the immediate contribution of the administration procedure to the efficacy of the intradural drug is calculated based on the event parameters and corresponding pharmacodynamic parameters of the procedure. To determine whether, during a particular epidural medication administration procedure, there is any residual medication effect in the epidural space that has not yet completely decayed due to one or more previous epidural medication administration procedures. If the judgment result is yes, and there is a drug interaction rule defined between the currently added drug type and the drug type that produces residual drug effect, then the instantaneous contribution calculated by the current addition operation or the previously existing residual drug effect is adjusted according to the drug interaction rule to obtain the adjusted instantaneous contribution or the adjusted residual drug effect. Taking into account the immediate contribution of all epidural drug administration procedures, including both adjusted and unadjusted immediate contributions, as well as all previously existing residual drug effects, including both adjusted and unadjusted residual drug effects, and considering the natural decay of drug efficacy over time, the overall efficacy status of the intradural drug solution at the current moment is determined, and this overall efficacy status is used as the drug efficacy status information.

[0031] Among them, event parameters refer to the set of key information used to describe each epidural medication administration operation, specifically including the time point of the operation, the specific type of medication used, and the total amount of medication injected. The purpose is to comprehensively record the history of human interventions affecting the state of the medication within the epidural space. Among them, efficacy characteristic parameters refer to the set of inherent attributes characterizing the pharmacological behavior of a specific type of epidural medication within the epidural space. These can be characterized by parameters including, but not limited to, the onset time, peak time, duration of action, half-life, and efficacy coefficient of the medication. The purpose is to quantify the potential impact of different medication types on efficacy. Among them, the immediate contribution refers to the quantified value of the direct, instantaneous impact of a single epidural medication administration operation on the overall efficacy of the medication within the epidural space after the operation is completed. The purpose is to assess the initial efficacy input of each administration procedure. Residual efficacy refers to the portion of efficacy remaining at the current time point that has not completely disappeared from the efficacy generated by one or more previous epidural administrations, aiming to account for the continuous effects of cumulative administration. Drug-liquid interaction rules define pre-defined laws or models governing the interaction of different types of epidural solutions when they are mixed in the epidural space, aiming to simulate and quantify the complex pharmacological effects of mixed drug use. Overall efficacy status refers to the quantitative representation of the total efficacy level of all effective drug components (including immediate contributions from previous administrations and their residues) in the epidural space at a specific time point, aiming to provide a comprehensive indicator reflecting the overall intensity of the current drug effect.

[0032] This application's approach establishes a complete dosing history by acquiring detailed event parameters for each epidural medication administration procedure, including administration time, medication type, and dosage. Based on these records, for each administration procedure, pharmacodynamic parameters for the corresponding medication type are obtained, quantifying the inherent pharmacological behavior of different medications. Furthermore, by combining the event parameters and pharmacodynamic parameters, the immediate contribution of each administration procedure to the intraluminal medication efficacy is calculated, providing an initial efficacy assessment for a single dose. Further, the approach determines whether there is any residual efficacy from previous administration that has not yet fully decayed, and considers the interaction rules between the currently administered medication and the residual efficacy medication type, adjusting the immediate contribution or residual efficacy accordingly. This allows the approach to simulate the complex pharmacological effects of mixed medication administration. Finally, the approach comprehensively considers the immediate contribution (including adjustments) from all previous administration procedures and all previously existing residual efficacy (including adjustments), taking into account the natural decay process of medication efficacy over time, to determine the overall efficacy status of the intradural medication at the current moment. This series of steps, organically combined, forms a method capable of comprehensively, dynamically, and accurately assessing the actual efficacy of intradural anesthetic solutions. By considering various factors such as dosing history, differences in solution type, drug-solution interactions, and time decay, this method overcomes the limitations of simple summation or considering only the last administration, providing more accurate information on pharmacodynamic status. This more accurate pharmacodynamic status information can serve as a reliable input for subsequent predictive calculations (e.g., adjusting computational parameters for predicting the risk of blockade plane shift), thereby improving the accuracy and reliability of the entire anesthetic efficacy assessment method and enabling more precise clinical decisions based on the assessment results.

[0033] As one embodiment of the present invention, the step of adjusting at least one computational parameter related to drug diffusion behavior or effect intensity in the predictive calculation process for the risk of displacement of the blocking plane due to the continuous influence of body position, based on drug efficacy status information, to obtain the adjusted computational parameter includes: Obtain drug efficacy status information; Based on drug efficacy status information, identify the dominant drug type or drug combination pattern in the current epidural space; Acquire and identify the preset pharmacological property set corresponding to the dominant drug liquid type or drug liquid combination mode; Based on a preset set of pharmacological characteristics, select a target operational parameter that is associated with the pharmacological behavior of the dominant drug type or drug combination mode from at least one operational parameter related to the diffusion behavior or intensity of the drug solution; Based on a preset set of pharmacological characteristics, the adjustment method for the selected target operational parameters is determined. The adjustment method includes the adjustment direction and adjustment range for adjusting the target operational parameters. The target operational parameters are adjusted using the determined adjustment method to obtain the adjusted operational parameters. The adjusted operational parameters are then used to predict the risk of displacement of the blocking plane due to the continuous influence of body position.

[0034] Identifying the dominant drug type or combination pattern within the current epidural space refers to determining the primary drug component or the mixture of different drug components in the epidural space based on pharmacodynamic status information. This determination can be made based on information such as the proportion, concentration, and duration of action of the drug components reflected in the pharmacodynamic status information. Its purpose is to provide a pharmacological basis for subsequent targeted parameter adjustments. The pre-set pharmacological characteristic set refers to a pre-stored set of pharmacological data related to different drug types or combinations. This set may include information such as the drug's diffusion coefficient, onset time, peak time, half-life, and interaction rules. Its purpose is to provide a basis for selecting and adjusting computational parameters. The computational parameters related to drug diffusion behavior or effect intensity refer to the mathematical parameters in the model used to predict and calculate the risk of blockade plane shift that affect the distribution and efficacy of the drug within the epidural space. This can include the diffusion rate constant, tissue permeability coefficient, receptor binding affinity, and metabolic clearance rate of the drug solution, with the aim of quantifying the pharmacological behavior of the drug solution. Selecting target computational parameters associated with the pharmacological behavior of the dominant drug solution type or combination mode refers to selecting parameters directly related to the diffusion, efficacy, and other behaviors of the drug solution or combination from all possible computational parameters based on the identified pharmacological characteristics of the dominant drug solution type or combination, with the aim of ensuring the targetedness and effectiveness of the adjustment. Determining the adjustment method for the selected target computational parameters refers to determining how to modify the value of the selected target computational parameters based on a preset set of pharmacological characteristics. This can be a specific numerical value, an adjustment ratio, an adjustment function, or a lookup table, used to indicate whether the parameter should be increased, decreased, or changed, and the specific amount of change, with the aim of guiding the precise adjustment of the parameters.

[0035] The reason this application's solution can achieve more precise adjustment of computational parameters in the prediction calculation process is that it does not employ a blind or empirical approach, but is based on an in-depth analysis of the current pharmacological environment within the epidural space. First, the acquired pharmacodynamic status information provides key data such as drug composition, concentration, and duration of action. Based on this information, the system can identify the dominant drug type or its combination pattern. Different drugs or combinations possess unique pharmacological properties, such as different diffusion rates, metabolic rates, and receptor affinities. These properties directly affect the distribution and intensity of the drug within the epidural space. By acquiring a preset set of pharmacological characteristics corresponding to the identified dominant drug type or combination pattern, the system obtains the theoretical basis for targeted adjustments. Therefore, based on this set of pharmacological characteristics, the solution can precisely select target computational parameters closely related to the pharmacological behavior of the current dominant drug or combination from among numerous computational parameters related to drug diffusion behavior or intensity. This selection mechanism ensures that the focus of adjustment is concentrated on the most critical and sensitive parameters, avoiding interference from irrelevant parameters. Furthermore, based on a pre-defined set of pharmacological characteristics, the scheme can determine specific adjustment methods for these selected target parameters, including the direction (increase or decrease) and magnitude of adjustment. This determination of adjustment methods is based on pharmacological principles and pre-defined data, rather than arbitrary settings, thus ensuring the scientific validity and rationality of the adjustments. Finally, the determined adjustment methods are applied to the target operational parameters to obtain adjusted parameters reflecting the current pharmacodynamic state, and these parameters are used for subsequent offset risk prediction calculations. It is through this progressive, pharmacologically based parameter selection and adjustment process that this scheme overcomes the blindness of parameter adjustment in existing technologies, enabling the prediction model to more accurately simulate real drug behavior, thereby improving the accuracy of retardation plane offset risk prediction. Combined with the steps for obtaining pharmacodynamic state information in the aforementioned scheme, this scheme can utilize dynamic and refined pharmacodynamic information to drive parameter adjustments, further enhancing the reliability of predictions.

[0036] As one embodiment of the present invention, based on a preset set of pharmacological characteristics, an adjustment method for the selected target operational parameters is determined. The adjustment method includes steps for adjusting the direction and magnitude of the target operational parameters: From the preset set of pharmacological characteristics, for each selected target operation parameter, the set of adjustment rules associated with that target operation parameter is retrieved. The set of adjustment rules defines the calculation logic used to determine the direction and magnitude of adjustment when the pharmacological state information indicates a specific pharmacological performance. Based on the pharmacological manifestations reflected by the obtained drug efficacy status information, the adjustment rules in the adjustment rule set are triggered; Based on the triggered adjustment rules and the calculation logic, the adjustment direction and adjustment magnitude of each target operation parameter are calculated, thereby determining the adjustment method for the selected target operation parameters.

[0037] The pre-defined pharmacological characteristic set refers to a pre-established knowledge base containing pharmacological behavior characteristics of various drug types or combination patterns and their association rules with the adjustment of operational parameters. This set can be implemented using databases, lookup tables, or rule engines, aiming to systematize pharmacological knowledge and provide a basis for parameter adjustment. The target operational parameters refer to one or more parameters directly related to drug diffusion behavior or effect intensity, which need to be adjusted based on pharmacodynamic status information during the calculation of the risk of displacement of the blocking plane due to the continuous influence of body position. These parameters may include drug diffusion rate constants, drug efficacy decay rate constants, and drug effect thresholds, aiming to simulate the actual behavior of the drug in the epidural space by adjusting these parameters. The adjustment method refers to the specific method or strategy used to change the value of the target operational parameters, which may include determining the direction and degree of parameter increase or decrease, aiming to guide specific parameter adjustment operations. The adjustment direction refers to the trend of the target operational parameter value change, i.e., increase or decrease, aiming to determine the qualitative direction of parameter adjustment. The adjustment magnitude refers to the amount or proportion of the target operational parameter value change, aiming to determine the quantitative degree of parameter adjustment. The adjustment rule set refers to a set of conditional-action rules defined within a pre-defined set of pharmacological characteristics for specific target operational parameters. These rules describe the computational logic for determining the adjustment direction and magnitude of the target operational parameter when pharmacodynamic state information indicates a specific pharmacological manifestation. They can be represented using conditional statements, decision trees, or rule lists, and their purpose is to link pharmacological manifestations with parameter adjustment logic. The computational logic refers to the specific algorithms or functional relationships defined within the adjustment rule set used to calculate the adjustment direction and magnitude of the target operational parameter based on pharmacodynamic state information. Expressed using mathematical formulas, lookup tables, or parameter adjustment functions, its purpose is to provide a quantitative calculation method for parameter adjustment; pharmacodynamic status information refers to data characterizing the current comprehensive efficacy status of the drug solution in the epidural space, which can be determined based on physiological processes or human intervention events (such as drug addition) that affect the characteristics of the drug solution, and its purpose is to provide input for the current pharmacological performance of the drug solution; pharmacological performance refers to the actual pharmacodynamic behavior or characteristics of the drug solution in the epidural space reflected by the pharmacodynamic status information, such as drug efficacy intensity, duration of action, diffusion capacity, etc., and its purpose is to serve as a condition for triggering adjustment rules.

[0038] This application's solution achieves refined adjustment of target operational parameters based on pharmacological state information by encoding pharmacological knowledge into a set of adjustment rules within a pre-defined set of pharmacological characteristics. First, for each selected target operational parameter, the system retrieves its associated set of adjustment rules from the pre-defined set of pharmacological characteristics. This set of rules predefines the calculation logic for determining the adjustment direction and magnitude under different pharmacological manifestations. It is precisely because this pre-established association between pharmacological manifestations and parameter adjustment logic is established that the subsequent adjustment process is based on established criteria. Second, the system triggers the corresponding adjustment rules in the set of adjustment rules based on the pharmacological manifestations reflected in the acquired pharmacological state information. This means that the corresponding adjustment rules are only activated when the pharmacological state information meets specific conditions, thus ensuring the targetedness and effectiveness of parameter adjustment. Finally, the system calculates the adjustment direction and magnitude of each target operational parameter based on the triggered adjustment rules and the defined calculation logic within them. This calculation logic corresponds to specific pharmacological manifestations and can accurately calculate how and to what extent the parameters should be adjusted based on the specific values ​​of the pharmacological state information. This parameter adjustment method, based on a set of pharmacological characteristics, pharmacodynamic status information, and a set of adjustment rules, allows for dynamic and precise adjustments to computational parameters, moving beyond simple preset values ​​or fixed proportions. These finely adjusted parameters are used in subsequent predictive calculations to more accurately simulate the diffusion behavior and intensity of the drug within the epidural space, thereby improving the accuracy of predicting the risk of displacement of the blocking plane due to persistent body position. Compared to fixed adjustments based solely on simple threshold judgments, this application integrates pharmacological knowledge into the parameter adjustment process by introducing a set of pharmacological characteristics and rule-based triggering and calculation logic based on pharmacodynamic status information. This makes the adjustments more scientific and targeted, overcoming the limitations of simple adjustment methods and improving the reliability of predictions.

[0039] As one embodiment of the present invention, the step of calculating the adjustment direction and adjustment magnitude of each target operation parameter according to the triggered adjustment rules and calculation logic includes: Based on the triggered adjustment rules, select the parameter adjustment function corresponding to the adjustment rules from the preset parameter adjustment function library; The pharmacological manifestations reflected in the drug efficacy status information are used as the input to the parameter adjustment function; By executing the parameter adjustment function, the adjustment direction and adjustment range of each target operation parameter are calculated.

[0040] The parameter adjustment function library refers to a pre-established collection of multiple parameter adjustment functions, which can be stored in the computer system's memory, hard disk, or other storage media. A parameter adjustment function is a program module or algorithm that encapsulates specific computational logic; it can receive pharmacological manifestations as input and output the adjustment direction and magnitude of the target operational parameters. The pharmacological manifestations reflected in the efficacy status information refer to the specific manifestations related to the actual pharmacological effects of the drug solution within the epidural space, as characterized by the efficacy status information. These manifestations can include the current overall efficacy level of the drug solution, the dominant drug solution type, the drug solution combination pattern, and the rate of efficacy decay.

[0041] This application's solution triggers adjustment rules based on the pharmacological manifestations reflected in the pharmacodynamic status information. Following these rules, a corresponding parameter adjustment function is selected from a pre-defined parameter adjustment function library. The pharmacological manifestations reflected in the pharmacodynamic status information are used as input to the parameter adjustment function. By executing the function, the adjustment direction and magnitude of each target parameter are calculated. This approach encapsulates complex computational logic within pre-defined functions, enabling rapid calculation through function calls and avoiding complex runtime logic checks, thus improving computational efficiency. This method of calling pre-defined functions from a function library, combined with calculation based on computational logic, achieves the goal of dynamically adjusting prediction model parameters according to pharmacodynamic status information, making the prediction of lag plane offset risk more accurate and timely.

[0042] As one embodiment of the present invention, the step of determining whether the difference meets the adjustment triggering condition includes: Obtain information about the current stage of surgery; Obtain real-time physiological status information of patients; Based on information about the surgical stage and physiological status, determine the applicable difference adjustment threshold; The difference is compared with the currently applicable difference adjustment threshold.

[0043] The current surgical stage information refers to the specific stage of the surgery, such as preoperative preparation, skin incision, tumor resection, lymph node dissection, and suturing. This information can be obtained through manual input by the doctor, access via the operating room information system interface, or automatically inferred based on the surgical duration and preset surgical procedures. Its purpose is to reflect the current surgical requirements for the depth of anesthesia and the stability of the block plane. The real-time patient physiological status information refers to the patient's current vital signs data, such as heart rate, blood pressure, respiratory rate, blood oxygen saturation, and body temperature. This information can be obtained by connecting to a patient monitor, manually inputting data, or through other physiological sensors. Its purpose is to reflect the patient's immediate response to and tolerance to anesthetic drugs. The currently applicable difference adjustment threshold is a critical value used to determine whether the difference between the actual dynamic change and the expected dynamic change of the block plane is large enough to trigger an association rule adjustment. This threshold can be obtained by consulting a preset threshold table, calculating based on a rule engine, or predicting through a machine learning model. Its purpose is to dynamically adjust the sensitivity of the trigger adjustment based on the surgical stage and the patient's physiological status.

[0044] This application's solution, by acquiring information about the current surgical stage, allows the system to understand the patient's tolerance to the anesthesia level; by acquiring real-time physiological information about the patient, the system can understand the patient's current physiological endurance. Based on these two types of information, the system no longer uses a fixed threshold, but dynamically calculates or finds a more suitable difference adjustment threshold for the current situation. Comparing the difference between the actual dynamic change and the expected dynamic change of the block level with this dynamically adjusted threshold allows for a more accurate determination of when subsequent association rule adjustments need to be triggered. This dynamic judgment mechanism avoids misjudgments or lags caused by fixed thresholds, making the subsequent process of adjusting association rules based on differences more accurate and timely. This combination of dynamic threshold judgment and difference-based association rule adjustment mechanism forms an effective means for refined and individualized management of epidural anesthesia effects.

[0045] As one embodiment of the present invention, the step of determining the overall efficacy status of the epidural fluid at the current moment, taking into account the natural decay process of the drug efficacy over time, and using this overall efficacy status as drug efficacy status information, includes: All currently effective efficacy contribution units are obtained. The efficacy contribution units include the instantaneous contribution generated by each epidural drug addition operation and the previously existing residual efficacy. Each efficacy contribution unit is associated with its initial effective efficacy value, the reference time point for efficacy establishment, and the drug-specific decay rate constant. Obtain the current point in time from which the overall performance status needs to be determined; For each efficacy contribution unit, based on its initial effective efficacy value, the reference time point for efficacy establishment, the drug-specific decay rate constant, and the current time point, the residual efficacy value of that efficacy contribution unit at the current time point is calculated using the following formula: E_residual = E_initial * exp(-k_decay * (T_current - T_reference)) Wherein, E_residual is the residual efficacy value, E_initial is the initial effective efficacy value, k_decay is the specific decay rate constant of the drug solution, T_current is the current time point, and T_reference is the reference time point for establishing efficacy; The residual efficacy values ​​of all efficacy contribution units at the current time point are summed to obtain the comprehensive efficacy status of the intradural fluid at the current moment, and this comprehensive efficacy status is used as the efficacy status information.

[0046] In this context, a drug efficacy contribution unit refers to the immediate contribution generated by each epidural drug administration or the previously existing residual efficacy. It can be represented using a data structure (such as an object, record, or data entry) to independently track and calculate the contribution of each efficacy source. The initial effective efficacy value refers to the efficacy intensity or level of a drug efficacy contribution unit at the reference time point where efficacy is established. It can be quantified using numerical values ​​(such as efficacy units, equivalent concentrations, or efficacy scores). The reference time point for efficacy establishment refers to the point at which a drug efficacy contribution unit begins to produce effective efficacy. The time point can be recorded using timestamps (such as the time when the additional operation was completed, or the time when the residual efficacy was identified); the drug-specific decay rate constant refers to the rate parameter of natural decay of the efficacy of a specific type of drug over time, which can be characterized by numerical values ​​(such as half-life, decay coefficient, or rate constant k), and this value is related to the pharmacological properties of the drug; the residual efficacy value refers to the remaining efficacy intensity or level of a drug efficacy contribution unit after natural decay at the current time point, which can be quantified by numerical values ​​(such as efficacy unit, equivalent concentration, or efficacy score).

[0047] This application provides a method for determining the overall efficacy status of intradural medication. The method first acquires all currently effective efficacy contribution units, representing all sources of efficacy within the epidural space, including the immediate contribution from newly added medication and the residual efficacy of previously added medication that has not yet fully decayed. Each efficacy contribution unit carries key information: an initial effective efficacy value, a reference time point for efficacy establishment, and a medication-specific decay rate constant. This information allows the system to independently track and simulate the dynamic changes of each efficacy source. Next, the current time point for which the efficacy status needs to be evaluated is acquired. For each efficacy contribution unit, using an exponential decay model, based on its initial effective efficacy value, the reference time point for efficacy establishment, the medication-specific decay rate constant, and the current time point, its residual efficacy value at the current time point is calculated. The exponential decay model accurately simulates the natural decay process of medication in vivo, while the medication-specific decay rate constant ensures that the decay characteristics of different medication types are reflected. Finally, the residual efficacy values ​​of all efficacy contribution units at the current time point are summed to obtain the overall efficacy status of the epidural fluid at the current moment. This summation method comprehensively considers all effective sources of efficacy and their respective decay, thus providing a more comprehensive and accurate efficacy assessment. This scheme decomposes each additional dose and residual efficacy into independent efficacy contribution units, assigning a specific decay rate constant and reference time point to each unit. An exponential decay model is used for calculation, enabling more precise quantification of fluid decay over time and effective integration of efficacy contributions from different sources. This precise efficacy status information is used to adjust the computational parameters in the calculation of block plane deviation risk. More accurate efficacy status information allows for more reasonable parameter adjustments, thereby improving the accuracy of deviation risk prediction. This accurate prediction result is ultimately used to guide anesthesia management, improving the reliability of anesthetic effect assessment.

[0048] like Figure 2 The system shown is a gastrointestinal tumor surgery anesthesia planning system, which includes: Temperature data acquisition module 201 is used to acquire body surface temperature data of multiple monitoring points distributed along a specific area of ​​the patient's torso; The posture information acquisition module 202 is used to acquire the patient's real-time trunk posture information; Baseline establishment module 203 is used to establish an individualized body surface temperature baseline associated with epidural anesthesia; The block plane assessment and risk prediction module 204 is used to assess the actual block plane of epidural anesthesia based on body surface temperature data, individualized body surface temperature baseline, real-time trunk posture information and preset association rules between body position and epidural drug diffusion trend, and predict the risk of block plane deviation due to continuous influence of body position, so as to obtain the actual block plane and deviation risk. The result output module 205 is used to output the actual hindrance plane and offset risk.

[0049] The proposed solution continuously collects the patient's surface temperature and trunk posture information through a temperature data acquisition module 201 and a posture information acquisition module 202. A baseline establishment module 203 establishes an individualized surface temperature baseline for the patient in advance or in real-time. An arrest plane assessment and risk prediction module 204 receives this data along with preset association rules and performs core calculations. It comprehensively analyzes changes in surface temperature relative to the baseline, the patient's current position, and known patterns of drug diffusion to determine the current actual arrest plane. Simultaneously, this module considers the possibility of continued positional influence and predicts the potential risk of arrest plane deviation. Finally, a results output module 205 presents the assessed actual arrest plane and predicted deviation risks to medical personnel. This collaborative approach enables the system to overcome the limitations of relying solely on indirect indicators, directly and dynamically assessing anesthetic effects and providing prospective risk warnings.

[0050] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for developing anesthesia plans for gastrointestinal tumor surgery, characterized in that, The method comprises the following steps: acquiring body surface temperature data of a plurality of monitoring points distributed in a specific region of the patient's torso; acquiring real-time torso posture information of the patient; establishing an individualized body surface temperature baseline related to epidural anesthesia; based on the body surface temperature data, the individualized body surface temperature baseline, the real-time torso posture information, and a preset association rule between body position and epidural drug solution diffusion trend, evaluating the actual block plane of epidural anesthesia and predicting the risk of shift of the block plane due to the continuous influence of body position, to obtain the actual block plane and the risk of shift; outputting the actual block plane and the risk of shift.

2. The method for developing anesthesia plans for gastrointestinal tumor surgery according to claim 1, characterized in that, The step of evaluating the actual block plane of epidural anesthesia and predicting the risk of shift of the block plane due to the continuous influence of body position based on the body surface temperature data, the individualized body surface temperature baseline, the real-time torso posture information, and a preset association rule between body position and epidural drug solution diffusion trend, to obtain the actual block plane and the risk of shift, comprises: acquiring the expected dynamic change of the block plane based on the real-time torso posture information and the currently effective preset association rule between body position and epidural drug solution diffusion trend; acquiring the dynamic change of the actual block plane based on the body surface temperature data and the individualized body surface temperature baseline; comparing the dynamic change of the actual block plane with the expected dynamic change of the block plane to determine the difference therebetween; if the difference meets the adjustment trigger condition, adjusting the drug solution diffusion characteristic parameter corresponding to the current real-time torso posture information in the association rule according to the difference to form an updated association rule; using the updated association rule and combining the body surface temperature data, the individualized body surface temperature baseline, and the real-time torso posture information to evaluate the actual block plane of epidural anesthesia and predict the risk of shift of the block plane due to the continuous influence of body position, to obtain the actual block plane and the risk of shift.

3. The method of claim 2, wherein the method is characterized by: The step of predicting the risk of shift of the block plane due to the continuous influence of body position comprises: acquiring drug efficacy state information representing the current efficacy state of the drug solution in the epidural space, the drug efficacy state information being determined according to physiological processes or artificial intervention events affecting the characteristics of the drug solution; adjusting at least one operation parameter related to the diffusion behavior or action strength of the drug solution in the prediction calculation process of the risk of shift of the block plane due to the continuous influence of body position according to the drug efficacy state information, to obtain an adjusted operation parameter; based on the adjusted operation parameter, performing the prediction calculation of the risk of shift of the block plane due to the continuous influence of body position, to obtain the risk of shift corresponding to the current efficacy state of the drug solution.

4. The method of claim 3, wherein the method is characterized by, The step of acquiring drug efficacy state information representing the current efficacy state of the drug solution in the epidural space, the drug efficacy state information being determined according to physiological processes or artificial intervention events affecting the characteristics of the drug solution, comprises: acquiring event parameters of previous epidural drug solution addition operations, the event parameters including the addition time, the type of added drug solution, and the dose of added drug solution of each previous addition operation; For each epidural liquid addition operation, an efficacy characteristic parameter corresponding to the type of liquid added in the operation is obtained, which represents the efficacy behavior of the type of liquid; For each epidural liquid addition operation, based on the event parameter of the operation and the corresponding efficacy characteristic parameter, the instantaneous contribution of the operation to the efficacy of the liquid in the epidural space is calculated; Determine whether there is a residual efficacy in the epidural space at a certain epidural liquid addition operation, which is generated by one or more previous epidural liquid addition operations and has not yet completely decayed; If the result of the determination is yes, and there is a liquid interaction rule defined between the type of liquid added in the current operation and the type of liquid that generates the residual efficacy, then according to the liquid interaction rule, the instantaneous contribution calculated by the current addition operation or the residual efficacy existing previously is adjusted to obtain the adjusted instantaneous contribution or the adjusted residual efficacy; Comprehensively consider the instantaneous contributions generated by all epidural liquid addition operations, including adjusted and unadjusted instantaneous contributions, and all previously existing residual efficacies, including adjusted and unadjusted residual efficacies, and take into account the natural decay process of liquid efficacy over time, to determine the comprehensive efficacy state of the liquid in the epidural space at the current time, and take the comprehensive efficacy state as the efficacy state information.

5. The method of claim 3, wherein the method is characterized by: The step of adjusting at least one operation parameter related to the diffusion behavior or intensity of the liquid in the process of predicting the risk of offset of the block plane caused by the continuous influence of body position according to the efficacy state information includes: Obtaining the efficacy state information; Based on the efficacy state information, identify the dominant type of liquid or combination mode of liquid in the epidural space at present; Obtain a set of preset pharmacological characteristics corresponding to the identified dominant type of liquid or combination mode of liquid; According to the set of preset pharmacological characteristics, select a target operation parameter associated with the pharmacological behavior of the dominant type of liquid or combination mode of liquid from the at least one operation parameter related to the diffusion behavior or intensity of the liquid; According to the set of preset pharmacological characteristics, determine the adjustment mode for the selected target operation parameter, which includes the adjustment direction and the adjustment amplitude for adjusting the target operation parameter; Apply the determined adjustment mode to the target operation parameter to adjust the target operation parameter to obtain the adjusted operation parameter, and use the adjusted operation parameter for predicting the risk of offset of the block plane caused by the continuous influence of body position.

6. The method for developing anesthesia plans for gastrointestinal tumor surgery according to claim 5, characterized in that, The step of determining the adjustment mode for the selected target operation parameter according to the set of preset pharmacological characteristics, which includes the adjustment direction and the adjustment amplitude for adjusting the target operation parameter, includes: For each selected target operation parameter, retrieve a set of adjustment rules associated with the target operation parameter from the set of preset pharmacological characteristics, which defines the calculation logic for determining the adjustment direction and the adjustment amplitude when the efficacy state information indicates a specific pharmacological performance; trigger an adjustment rule in the adjustment rule set according to the pharmacological manifestation reflected by the acquired drug efficacy state information; calculate the adjustment direction and adjustment amplitude of each target operation parameter according to the triggered adjustment rule and the calculation logic, so as to determine the adjustment mode for the selected target operation parameter.

7. The method for developing anesthesia plans for gastrointestinal tumor surgery according to claim 6, characterized in that, The step of calculating the adjustment direction and adjustment amplitude of each target operation parameter according to the triggered adjustment rule and the calculation logic comprises: selecting a parameter adjustment function corresponding to the adjustment rule from a preset parameter adjustment function library according to the triggered adjustment rule; taking the pharmacological manifestation reflected in the drug efficacy state information as the input of the parameter adjustment function; calculating the adjustment direction and adjustment amplitude of each target operation parameter by executing the parameter adjustment function.

8. The method for developing anesthesia plans for gastrointestinal tumor surgery according to claim 2, characterized in that, The step of judging whether the difference meets the adjustment triggering condition comprises: acquiring current surgery stage information; acquiring real-time physiological state information of the patient; determining a currently applicable difference adjustment threshold according to the surgery stage information and the physiological state information; comparing the difference with the currently applicable difference adjustment threshold.

9. The method for developing anesthesia plans for gastrointestinal tumor surgery according to claim 4, characterized in that, The step of determining the comprehensive efficacy state of the epidural cavity drug at the current time point by taking into account the natural decay process of the drug efficacy over time, and taking the comprehensive efficacy state as the drug efficacy state information comprises: acquiring all currently effective drug efficacy contribution units, the drug efficacy contribution units including an immediate contribution amount generated by a previous epidural drug addition operation and a residual drug efficacy previously existing, and each drug efficacy contribution unit being associated with an initial effective drug efficacy value, a reference time point of drug efficacy establishment, and a drug-specific decay rate constant; acquiring a current time point for which the comprehensive efficacy state needs to be determined; for each drug efficacy contribution unit, calculating a residual drug efficacy value of the drug efficacy contribution unit at the current time point based on the initial effective drug efficacy value, the reference time point of drug efficacy establishment, the drug-specific decay rate constant, and the current time point; accumulating the residual drug efficacy values of all the drug efficacy contribution units at the current time point to obtain the comprehensive efficacy state of the epidural cavity drug at the current time point, and taking the comprehensive efficacy state as the drug efficacy state information.

10. A system for developing anesthesia plans for gastrointestinal tumor surgery, characterized in that, The system comprises: a temperature data acquisition module configured to acquire body surface temperature data of a plurality of monitoring points distributed along a specific region of a patient's torso; a posture information acquisition module configured to acquire real-time torso posture information of the patient; a baseline establishment module configured to establish an individualized body surface temperature baseline related to epidural anesthesia; a block plane evaluation and risk prediction module configured to evaluate an actual block plane of epidural anesthesia and predict a risk of shift of the block plane due to a body position based on the body surface temperature data, the individualized body surface temperature baseline, the real-time torso posture information, and a preset association rule between body positions and epidural drug diffusion trends, to obtain the actual block plane and the risk of shift; a result output module configured to output the actual block plane and the risk of shift.

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