A perioperative nursing system and method for abdominal aortic aneurysm

Abstract

The present application belongs to the technical field of medical care, and particularly relates to a perioperative nursing system and method for abdominal aortic aneurysm. The present application divides the perioperative period into preoperative stage, intraoperative stage and postoperative stage, and presets different parameter weight sets and risk trigger thresholds for different stages, so that the risk assessment can be analyzed according to the physiological characteristics of different stages, thereby improving the accuracy and adaptability of risk identification. The present application analyzes the change trend of continuously collected physiological data, and generates physiological change data such as aneurysm structure change rate, blood flow dynamics change rate, abdominal pressure change rate and perfusion change rate, so that the risk assessment is no longer dependent on static data at a single time point, but is analyzed based on the dynamic change trend of physiological indexes, thereby more accurately reflecting the real physiological state change of the patient.

Description

Technical Field

[0001] This invention belongs to the field of medical and nursing technology, specifically relating to a perioperative nursing system and method for abdominal aortic aneurysm. Background Technology

[0002] Abdominal aortic aneurysm is a common and potentially dangerous vascular disease, characterized by localized dilation of the abdominal aorta. It is prone to rupture and massive hemorrhage, severely threatening the patient's life. The perioperative period encompasses the entire process from surgical preparation to postoperative recovery, including preoperative assessment and preparation, surgical procedure, and postoperative monitoring and recovery. During this period, physiological indicators such as the patient's hemodynamic status, aneurysm structural changes, intra-abdominal pressure, and organ perfusion may fluctuate rapidly, placing extremely high demands on the quality of perioperative nursing care.

[0003] Current perioperative nursing methods rely heavily on the experience of medical staff for monitoring and judgment, and are usually based on single indicators such as blood pressure, heart rate, and urine output. They lack comprehensive analysis of multidimensional physiological indicators and real-time risk assessment methods. It is difficult to monitor and intervene in key risk factors at different perioperative stages, and it is impossible to dynamically adjust nursing strategies. This can easily lead to delayed detection of high-risk events and increase the incidence of intraoperative and postoperative complications. Summary of the Invention

[0004] The purpose of this invention is to provide a perioperative nursing system and method for abdominal aortic aneurysms, which can improve the precision of nursing care, reduce the incidence of perioperative complications, and provide reliable decision support for medical staff.

[0005] The specific technical solution adopted by this invention is as follows: A perioperative nursing method for abdominal aortic aneurysm includes: The perioperative period is divided into the preoperative stage, the intraoperative stage and the postoperative stage, and corresponding parameter weighting and initial risk triggering thresholds are preset for each stage. Physiological data of patients are continuously collected at preset time intervals during the perioperative period. Physiological change data are obtained based on the physiological data, including the rate of change of tumor structure, the rate of change of hemodynamics, the rate of change of abdominal pressure, and the rate of change of perfusion. Within the current stage, the risk value of the current stage is obtained by recombining the parameter weights of the corresponding stage and combining them with the corresponding physiological change data. Establish a stage benchmark risk range within the current stage. When the stage risk value remains stable over multiple consecutive collection periods, use the statistical mean of the current stage risk value as the new benchmark risk value, and obtain the corresponding stage risk trigger threshold based on the benchmark risk value. When the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, the stage enhancement mode is executed, the corresponding parameter weight reassembly in the current stage is adjusted, and the original parameter weight reassembly is restored when the risk value returns to the baseline risk range. The real-time risk level is obtained based on the current stage risk value and output to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold of the corresponding stage, a nursing prompt message is generated.

[0006] In a preferred embodiment, the perioperative period is divided into a preoperative stage, an intraoperative stage, and a postoperative stage, and corresponding parameter weighting and initial risk triggering thresholds are preset for each stage, including: Based on the surgical procedure timeline, the patient management process is divided into the preoperative stage, the intraoperative stage, and the postoperative stage. The preoperative stage is the time interval from when the patient enters the surgical preparation state to before the start of the surgery; the intraoperative stage is the time interval from the start of the surgery to the end of the surgery; and the postoperative stage is the time interval from the end of the surgery to the termination of perioperative monitoring. In the preoperative stage, preoperative parameter weighting is preset, and preoperative initial risk triggering threshold is preset. The preoperative parameter weighting includes preoperative structural weighting coefficient, preoperative blood flow weighting coefficient, preoperative abdominal pressure weighting coefficient, and preoperative perfusion weighting coefficient. During the intraoperative phase, intraoperative parameter weighting is preset, and intraoperative initial risk triggering threshold is preset. The intraoperative parameter weighting includes intraoperative structural weighting coefficient, intraoperative blood flow weighting coefficient, intraoperative abdominal pressure weighting coefficient, and intraoperative perfusion weighting coefficient. In the postoperative stage, the postoperative parameter weighting is preset, and the initial postoperative risk trigger threshold is preset. The postoperative parameter weighting includes the postoperative structural weighting coefficient, the postoperative blood flow weighting coefficient, the postoperative abdominal pressure weighting coefficient, and the postoperative perfusion weighting coefficient.

[0007] In a preferred embodiment, physiological data of the patient are continuously collected at preset time intervals during the perioperative period. Physiological change data are obtained based on this data, including the rate of change in tumor structure, the rate of change in hemodynamics, the rate of change in abdominal pressure, and the rate of change in perfusion, including: During the perioperative period, physiological data of patients were continuously collected at preset collection time intervals. The physiological data included the maximum diameter of the tumor, the thickness of the tumor wall, systolic blood pressure, diastolic blood pressure, heart rate, intra-abdominal pressure, mean arterial pressure, urine output, and blood lactate. Based on the maximum diameter and wall thickness data of the tumor, the corresponding change values ​​and directions are obtained, and the tumor structure change rate is generated. Based on systolic blood pressure data, diastolic blood pressure data, and heart rate data, obtain the corresponding change values ​​and directions of change, and generate the hemodynamic change rate; Based on the intra-abdominal pressure data, the corresponding change value and direction of change are obtained, and the rate of change of intra-abdominal pressure is generated. Based on mean arterial pressure data, urine output data, and blood lactate data, obtain the corresponding change values ​​and directions, and generate the perfusion change rate; Physiological change data were generated by summarizing the rates of change in tumor structure, hemodynamics, abdominal pressure, and perfusion.

[0008] In a preferred embodiment, within the current stage, the risk value for the current stage is obtained based on the parameter weighting of the corresponding stage and in conjunction with the corresponding physiological change data, including: Identify the current stage based on the patient's current perioperative timeline; Obtain the corresponding parameter weights and reorganize them according to the current stage; Based on the physiological data corresponding to the current stage, and combined with the corresponding parameter weighting, the risk value for the current stage is obtained; If the current stage is the preoperative stage, the preoperative structural weight coefficient and preoperative blood flow weight coefficient are obtained from the corresponding parameter weight recombination, and the tumor structure change rate and hemodynamic change rate are extracted according to the corresponding physiological data, and weighted fusion is performed to obtain the preoperative stage risk value. If the current stage is the intraoperative stage, the intraoperative blood flow weight coefficient, intraoperative abdominal pressure weight coefficient and intraoperative perfusion weight coefficient are obtained from the corresponding parameter weighting recombination. Based on the corresponding physiological data, the hemodynamic change rate, abdominal pressure change rate and perfusion change rate are extracted and weighted to obtain the intraoperative stage risk value. If the current stage is the postoperative stage, the postoperative abdominal pressure weight coefficient and postoperative perfusion weight coefficient are obtained from the corresponding parameter weighting reassembly, and the abdominal pressure change rate and perfusion change rate are extracted based on the corresponding physiological data, and weighted fusion is performed to obtain the postoperative stage risk value.

[0009] In a preferred embodiment, a baseline risk range is established within the current stage. When the stage risk value remains stable over multiple consecutive data collection periods, the statistical mean of the current stage risk value is used as the new baseline risk value. The corresponding risk trigger threshold is then obtained based on this baseline risk value, including: Identify the current stage based on the patient's current perioperative time point, and establish a stage baseline risk interval within the current stage; Obtain a preset data collection time interval, continuously acquire stage risk assessment values ​​according to the preset data collection time interval, and form a stage risk value set in the order of data collection time; Compare the stage risk values ​​corresponding to two adjacent collection periods in the stage risk value set to obtain the risk value change range between each adjacent collection period. When the change in risk value within multiple consecutive collection periods is less than the preset stable change range, the corresponding multiple consecutive collection periods are determined as the stage risk stabilization period. Obtain all stage risk values ​​corresponding to the stable period of stage risk, and form a stable period risk value set; The stable cycle mean of the stable cycle risk value set is obtained from all the stage risk values ​​in the stable cycle risk value set, and the stable cycle mean is marked as the benchmark risk value for the current stage. Obtain the risk trigger threshold for the corresponding stage based on the benchmark risk value.

[0010] In a preferred embodiment, the risk trigger threshold for the corresponding stage is obtained based on a benchmark risk value, including: Obtain the upper and lower boundary values ​​of the stage benchmark risk range; Based on the numerical distance between the benchmark risk value and the upper and lower boundary values ​​of the stage benchmark risk interval, the threshold offset range of the preset initial risk trigger threshold for the current stage relative to the benchmark risk value is obtained. Based on the preset initial risk trigger threshold for the current stage, obtain the current offset position of the initial risk trigger threshold relative to the baseline risk value; When the current offset position is within the stage baseline risk range, the initial risk trigger threshold is adjusted according to the threshold offset range, so that the adjusted initial risk trigger threshold is moved to a preset position outside the stage baseline risk range, and the adjusted initial risk trigger threshold is marked as the risk trigger threshold of the current stage.

[0011] In a preferred embodiment, when the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, a stage enhancement mode is executed to adjust the parameter weight reassembly corresponding to the current stage. When the risk value recovers to within the baseline risk range, the original parameter weight reassembly is restored, including: Obtain the stage risk value set, compare the stage risk value corresponding to multiple consecutive collection periods in the stage risk value set with the risk trigger threshold of the current stage, and determine that the current stage is in a risk over-threshold state when the stage risk value of multiple consecutive collection periods is greater than the risk trigger threshold. When the risk threshold is exceeded, the current stage enhancement mode is activated, and the parameter weights corresponding to the current stage are adjusted according to the preset weight adjustment rules. The stage risk value is obtained according to the preset collection time interval, and it is determined whether the stage risk value has entered the stage benchmark risk range. When the stage risk value re-enters the stage benchmark risk range and maintains a preset stable period, the stage enhancement mode is terminated, and the original parameter weights preset for the current stage are restored.

[0012] In a preferred embodiment, a real-time risk level is obtained based on the current stage risk value and output to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold for the corresponding stage, a nursing prompt message is generated, including: Obtain the real-time risk level for the corresponding data collection period based on the current stage risk value; The real-time risk level is sent to the nursing terminal through the monitoring system and displayed on the nursing terminal; Obtain the stage risk trigger threshold corresponding to the current stage, and compare the real-time risk level with the stage risk trigger threshold; When the real-time risk level exceeds the stage risk trigger threshold, a corresponding nursing prompt message is generated and sent to the nursing terminal.

[0013] The present invention also provides a perioperative nursing system for abdominal aortic aneurysms, used in the above-mentioned perioperative nursing methods for abdominal aortic aneurysms, comprising: The phase division module is used to divide the perioperative period into the preoperative phase, intraoperative phase and postoperative phase, and to preset the corresponding parameter weighting and initial risk triggering threshold for each phase. The physiological change module is used to continuously collect the patient's physiological data at preset time intervals during the perioperative period and obtain physiological change data based on the physiological data. The physiological change data includes the rate of change of tumor structure, the rate of change of hemodynamics, the rate of change of abdominal pressure, and the rate of change of perfusion. The stage risk module is used to obtain the risk value of the current stage based on the parameter weighting of the corresponding stage and the corresponding physiological change data. The trigger threshold module is used to establish a stage baseline risk range within the current stage. When the stage risk value remains stable within multiple consecutive collection cycles, the statistical mean of the current stage risk value is used as the new baseline risk value, and the risk trigger threshold for the corresponding stage is obtained based on the baseline risk value. The weight adjustment module is used to execute the stage enhancement mode when the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, and adjust the corresponding parameter weight reassembly in the current stage. When the risk value recovers to the baseline risk range, the original parameter weight reassembly is restored. The nursing alert module is used to obtain the real-time risk level based on the current stage risk value and output it to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold of the corresponding stage, a nursing alert message is generated.

[0014] And, a perioperative care terminal for abdominal aortic aneurysm, comprising: One or more processors; A storage device on which one or more programs are stored; When one or more programs are executed by one or more processors, the one or more processors implement perioperative care methods for abdominal aortic aneurysms.

[0015] The technical effects achieved by this invention are as follows: This invention divides the perioperative period into preoperative, intraoperative, and postoperative stages, and pre-sets different parameter weightings and risk trigger thresholds for each stage. This allows risk assessment to be tailored to the physiological characteristics of each stage, thereby improving the accuracy and adaptability of risk identification. By analyzing the changing trends of continuously collected physiological data and generating physiological change data such as tumor structure change rate, hemodynamic change rate, abdominal pressure change rate, and perfusion change rate, risk assessment no longer relies solely on static data at a single time point, but is based on the dynamic changing trends of physiological indicators, thus more accurately reflecting the patient's true physiological state changes. This invention establishes a phased baseline risk range and dynamically updates the risk trigger threshold based on the phased risk value within a stable period. This allows the risk threshold to adaptively adjust according to the patient's current physiological state, avoiding misjudgments caused by fixed thresholds and improving the stability and reliability of risk assessment. By setting a phased reinforcement mode, when a sustained increase in risk is detected, parameter weights are automatically adjusted, enhancing the system's ability to identify abnormal risk changes. The original weight settings are automatically restored after the risk returns to normal, ensuring the system's flexibility and stability. By outputting real-time risk levels to the nursing terminal and generating nursing prompts, medical staff can promptly obtain information on changes in patient risk and take targeted nursing measures, thereby improving the timeliness and safety of perioperative nursing management. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method provided by the present invention; Figure 2 This is a system module diagram provided by the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0020] Furthermore, the present invention will be described in detail with reference to the schematic diagrams. When describing the embodiments of the present invention in detail, the schematic diagrams are merely examples for ease of explanation and should not limit the scope of protection of the present invention.

[0021] Please see the appendix Figure 1 As shown, a perioperative nursing method for abdominal aortic aneurysm is provided, including: S1. Divide the perioperative period into the preoperative stage, the intraoperative stage and the postoperative stage, and preset the corresponding parameter weighting and initial risk triggering threshold for each stage. S2. Collect the patient’s physiological data continuously at preset time intervals during the perioperative period, and obtain physiological change data based on the physiological data. The physiological change data includes the rate of change of tumor structure, the rate of change of hemodynamics, the rate of change of abdominal pressure, and the rate of change of perfusion. S3. Within the current stage, the risk value of the current stage is obtained by recombining the parameter weights of the corresponding stage and combining them with the corresponding physiological change data. S4. Establish a stage benchmark risk range within the current stage. When the stage risk value remains stable within multiple consecutive collection periods, take the statistical mean of the current stage risk value as the new benchmark risk value, and obtain the risk trigger threshold for the corresponding stage based on the benchmark risk value. S5. When the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, the stage enhancement mode is executed, the corresponding parameter weight reorganization in the current stage is adjusted, and the original parameter weight reorganization is restored when the risk value returns to the baseline risk range. S6. Obtain the real-time risk level based on the current stage risk value and output it to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold of the corresponding stage, generate a nursing prompt message.

[0022] As described in steps S1 to S6 above, the perioperative period is divided into preoperative, intraoperative, and postoperative stages based on the timeline of the surgical procedure. Since the sources of physiological risks and monitoring priorities differ across stages, corresponding parameter weighting and initial risk trigger thresholds are preset for each stage. This ensures that clinically significant physiological parameters are highlighted during risk assessment, thereby improving the targeting and accuracy of risk identification. During the perioperative period, patients are continuously monitored at preset collection intervals, collecting multiple physiological data, including maximum tumor diameter, tumor wall thickness, blood pressure, heart rate, intra-abdominal pressure, and perfusion-related data. The physiological data from adjacent collection cycles are then analyzed. Intermittent processing is performed to acquire changes in various physiological indicators, further generating physiological change data reflecting the degree of change per unit time. This physiological change data includes the rate of change in tumor structure, hemodynamics, abdominal pressure, and perfusion. Based on the patient's current perioperative stage, a pre-set parameter weighting system for that stage is invoked, and combined with the currently acquired physiological change data for comprehensive processing. By weighted fusion of various rate of change data, the risk value for the current stage is obtained, thereby achieving a quantitative assessment of the patient's current risk status. To avoid interference from short-term fluctuations in risk assessment, a stage baseline risk interval is established within the current stage, and the stability of the stage risk value across multiple consecutive acquisition cycles is assessed. When the risk value of a phase within a collection period changes relatively little and remains relatively stable, the statistical mean of the risk values ​​within that stable period is determined as the new baseline risk value. Based on this, the risk trigger threshold for that phase is updated to adapt to the patient's current physiological state. When the current phase risk value exceeds the corresponding phase's risk trigger threshold for multiple consecutive collection periods, the patient's risk status is determined to be abnormally elevated. At this point, a phase enhancement mode is activated. In this mode, the parameter weights for the current phase are adjusted according to preset rules, increasing the weight of physiological indicators closely related to risk changes in risk calculation. This enhances the system's sensitivity to identifying abnormal risk changes. When the risk value falls back to the baseline, the system continues to enhance its sensitivity. When the baseline risk range is maintained and remains stable, the enhanced phase mode is terminated and the original parameter weighting is restored. A corresponding real-time risk level is generated based on the current phase risk value, and this level is output to the nursing terminal for display via the monitoring system. When the real-time risk level exceeds the risk trigger threshold for the corresponding phase, a nursing alert is automatically generated, prompting medical staff to take timely and appropriate nursing interventions. This achieves proactive early warning and decision support for the patient's risk status. By dividing the perioperative period into preoperative, intraoperative, and postoperative phases, and presetting different parameter weightings and risk trigger thresholds for different phases, risk assessment can be tailored to the physiological characteristics of each phase, thereby improving the accuracy and adaptability of risk identification.By analyzing the changing trends of continuously collected physiological data and generating physiological change data such as tumor structure change rate, hemodynamic change rate, abdominal pressure change rate, and perfusion change rate, risk assessment no longer relies solely on static data at a single time point, but is based on the dynamic changing trends of physiological indicators. This allows for a more accurate reflection of the patient's true physiological state. By establishing a phased baseline risk range and dynamically updating the risk trigger threshold based on the phased risk value within a stable period, the risk threshold can adaptively adjust according to the patient's current physiological state, avoiding misjudgments caused by fixed thresholds and improving the stability and reliability of risk assessment. By setting a phased reinforcement mode, when a sustained increase in risk is detected, parameter weights are automatically adjusted, enhancing the system's ability to identify abnormal risk changes. The original weight settings are automatically restored after the risk returns to normal, ensuring the system's flexibility and stability. By outputting real-time risk levels to the nursing terminal and generating nursing prompts, medical staff can promptly obtain information on changes in patient risk and take targeted nursing measures, thereby improving the timeliness and safety of perioperative nursing management.

[0023] In a preferred embodiment, the perioperative period is divided into a preoperative stage, an intraoperative stage, and a postoperative stage, and corresponding parameter weighting and initial risk triggering thresholds are preset for each stage, including: S101. Based on the surgical implementation time, the patient management process is divided into the preoperative stage, the intraoperative stage, and the postoperative stage. The preoperative stage is the time interval from when the patient enters the surgical preparation state to before the start of the surgery; the intraoperative stage is the time interval from the start of the surgery to the end of the surgery; and the postoperative stage is the time interval from the end of the surgery to the termination of perioperative monitoring. S102. In the preoperative stage, the preoperative parameter weighting is preset, and the preoperative initial risk triggering threshold is preset. The preoperative parameter weighting includes the preoperative structural weighting coefficient, the preoperative blood flow weighting coefficient, the preoperative abdominal pressure weighting coefficient, and the preoperative perfusion weighting coefficient. S103. During the intraoperative phase, the intraoperative parameter weighting is preset, and the intraoperative initial risk triggering threshold is preset. The intraoperative parameter weighting includes the intraoperative structural weighting coefficient, the intraoperative blood flow weighting coefficient, the intraoperative abdominal pressure weighting coefficient, and the intraoperative perfusion weighting coefficient. S104. In the postoperative stage, the postoperative parameter weighting is preset, and the postoperative initial risk trigger threshold is preset. The postoperative parameter weighting includes the postoperative structural weighting coefficient, the postoperative blood flow weighting coefficient, the postoperative abdominal pressure weighting coefficient, and the postoperative perfusion weighting coefficient.

[0024] As described in steps S101 to S104 above, the perioperative management process for patients is divided into stages based on key time points during the surgical procedure. This process is categorized into preoperative, intraoperative, and postoperative stages. The preoperative stage encompasses the period from when the patient enters surgical preparation mode until the start of surgery; the intraoperative stage extends from the start to the end of surgery; and the postoperative stage lasts from the end of surgery until the termination of perioperative monitoring. In the preoperative stage, preoperative parameter weighting and initial risk trigger thresholds are preset. Specifically, based on the key risk factors considered in the preoperative management of abdominal aortic aneurysms, the importance of structural parameters, hemodynamic parameters, abdominal pressure parameters, and perfusion parameters are assessed, and then categorized according to risk relevance. Different parameters are assigned different weight levels, thus forming a preoperative parameter weighting system. In the preoperative stage, because the stability of the tumor structure and hemodynamic status have a significant impact on surgical risk, the weights of preoperative structural parameters and preoperative blood flow parameters are set to relatively high levels, while the weights of preoperative abdominal pressure parameters and preoperative perfusion parameters are set to relatively low levels. After completing the weighting, a safe range for risk assessment results is preset based on the routine physiological monitoring range and historical clinical risk data in the preoperative stage. An initial preoperative risk trigger threshold is set outside the safe range. When the risk assessment result exceeds this threshold, it is determined that there is a potential risk, thereby achieving preoperative risk warning. In the intraoperative stage, an intraoperative parameter weighting system is preset, and... Intraoperative initial risk trigger thresholds are crucial because changes in hemodynamics and intra-abdominal pressure significantly impact the stability of vital signs during surgery. Therefore, when setting parameter weights, the weights of blood flow and intra-abdominal pressure parameters are increased, while the weights of structural parameters are relatively decreased. This allows risk assessment to more sensitively reflect intraoperative blood flow fluctuations and intraoperative pressure changes. Furthermore, based on common vital sign fluctuations during surgery and intraoperative monitoring experience, a normal fluctuation range for intraoperative risk assessment results is defined, and an initial intraoperative risk trigger threshold is set outside this range. This enables timely identification of abnormal intraoperative risk states. Postoperative parameter weighting and initial postoperative risk trigger thresholds are pre-set, gradually shifting the patient's primary risk source from structural stability... The qualitative shift is towards changes in tissue perfusion status and intra-abdominal pressure. Therefore, when setting parameter weights, the weights of intra-abdominal pressure and perfusion parameters are increased, while the weights of structural parameters are relatively reduced. This allows the risk assessment to focus on the patient's postoperative circulatory recovery and organ perfusion status. At the same time, based on the range of changes in common physiological indicators during postoperative recovery monitoring, a safe range for the risk assessment results is set, and an initial postoperative risk trigger threshold is set outside this safe range. When the risk assessment result exceeds this threshold, a postoperative risk warning is triggered. Corresponding parameter weighting and risk trigger thresholds are established for different stages of the perioperative period, enabling the risk assessment model to automatically adjust its focus according to the characteristics of each stage, thereby achieving a staged and dynamic assessment of the patient's risk status.

[0025] In a preferred embodiment, physiological data of the patient are continuously collected at preset time intervals during the perioperative period, and physiological change data are obtained based on the physiological data. These physiological change data include the rate of change in tumor structure, the rate of change in hemodynamics, the rate of change in abdominal pressure, and the rate of change in perfusion, including: S201. During the perioperative period, the patient's physiological data are continuously collected at preset collection time intervals. The physiological data include the maximum diameter of the tumor, the thickness of the tumor wall, systolic blood pressure, diastolic blood pressure, heart rate, intra-abdominal pressure, mean arterial pressure, urine output, and blood lactate. S202. Based on the maximum diameter data and wall thickness data of the tumor, obtain the corresponding change value and direction of change, and generate the tumor structure change rate. S203. Based on the systolic blood pressure data, diastolic blood pressure data, and heart rate data, obtain the corresponding change values ​​and directions of change, and generate the hemodynamic change rate. S204. Obtain the corresponding change value and direction of change based on the intra-abdominal pressure data, and generate the rate of change of intra-abdominal pressure. S205. Based on the mean arterial pressure data, urine output data, and blood lactate data, obtain the corresponding change values ​​and directions of change, and generate the perfusion change rate; S206. Physiological change data are formed by summarizing the rate of change in tumor structure, rate of change in hemodynamics, rate of change in abdominal pressure, and rate of change in perfusion.

[0026] As described in steps S201 to S206 above, the patient is continuously monitored during the perioperative period at preset collection time intervals, and multiple physiological data are collected. These collected physiological data include the maximum diameter of the tumor, tumor wall thickness, systolic blood pressure, diastolic blood pressure, heart rate, intra-abdominal pressure, mean arterial pressure, urine output, and blood lactate levels. By continuously collecting these multidimensional physiological indicators, a physiological data sequence arranged in chronological order can be formed. Based on the continuously collected maximum diameter and wall thickness data of the tumor, data from adjacent collection cycles are compared and processed to calculate the numerical difference between the current collection cycle and the previous collection cycle, thereby determining the maximum diameter of the tumor. The rate and direction of change of the maximum diameter and tumor wall thickness per unit time were analyzed. Based on this, according to the direction and magnitude of the rate of change of the maximum diameter and tumor wall thickness, corresponding weight coefficients were obtained through a pre-set parameter weight lookup table. These coefficients were then weighted and fused with the change values ​​of each parameter to generate a single tumor structure change rate value reflecting the overall structural changes of the tumor. Hemodynamic status was processed based on systolic blood pressure, diastolic blood pressure, and heart rate data. Specifically, by comparing the differences in systolic blood pressure, diastolic blood pressure, and heart rate values ​​between the current and previous acquisition cycles, the rate and direction of change of each of the three indicators per unit time were determined, and this was then calculated using a pre-set parameter weight lookup table. The method obtains the corresponding weighting coefficients, combines them with the changes in the three indicators, and performs weighted fusion processing to generate a hemodynamic change rate value that comprehensively reflects the overall hemodynamic changes. Intra-abdominal pressure changes are monitored based on intra-abdominal pressure data. By calculating the difference in intra-abdominal pressure values ​​between the current and previous collection cycles, the change value and direction of intra-abdominal pressure per unit time are determined, and the obtained change value is used as the intra-abdominal pressure change rate to reflect the trend of intra-abdominal pressure changes. The patient's tissue perfusion status is processed based on mean arterial pressure data, urine output data, and blood lactate data. Specifically, this is achieved by calculating the differences in the values ​​of the three indicators between the current and previous collection cycles. The rate and direction of change of mean arterial pressure, urine output, and blood lactate per unit time were determined. Based on the direction and magnitude of change of each indicator, the corresponding weight coefficients were obtained by looking up a table. Then, the change values ​​of each indicator were combined and weighted to generate a single perfusion rate value that reflects the overall tissue perfusion change. The obtained tumor structure change rate, hemodynamic change rate, abdominal pressure change rate, and perfusion change rate were summarized and integrated to form physiological change data that characterizes the overall physiological state of the patient. This can transform complex multidimensional physiological monitoring data into change rate data with clear trend characteristics, thereby realizing a dynamic quantitative description of the changes in the patient's physiological state.

[0027] In a preferred embodiment, within the current stage, the risk value for the current stage is obtained based on the parameter weighting of the corresponding stage and in conjunction with the corresponding physiological change data, including: S301. Identify the current stage based on the patient's current perioperative time point; S302. Obtain the corresponding parameter weight reorganization according to the current stage; S303. Obtain the risk value for the current stage based on the physiological data corresponding to the current stage and in combination with the corresponding parameter weighting. If the current stage is the preoperative stage, the preoperative structural weight coefficient and preoperative blood flow weight coefficient are obtained from the corresponding parameter weight recombination, and the tumor structure change rate and hemodynamic change rate are extracted according to the corresponding physiological data, and weighted fusion is performed to obtain the preoperative stage risk value. If the current stage is the intraoperative stage, the intraoperative blood flow weight coefficient, intraoperative abdominal pressure weight coefficient and intraoperative perfusion weight coefficient are obtained from the corresponding parameter weighting recombination. Based on the corresponding physiological data, the hemodynamic change rate, abdominal pressure change rate and perfusion change rate are extracted and weighted to obtain the intraoperative stage risk value. If the current stage is the postoperative stage, the postoperative abdominal pressure weight coefficient and postoperative perfusion weight coefficient are obtained from the corresponding parameter weighting reassembly, and the abdominal pressure change rate and perfusion change rate are extracted based on the corresponding physiological data, and weighted fusion is performed to obtain the postoperative stage risk value.

[0028] As described in steps S301 to S303 above, the patient's current perioperative stage is identified based on the current perioperative time point. Since the physiological changes at different perioperative stages differ significantly—for example, the preoperative stage focuses on tumor structural stability and baseline blood flow, the intraoperative stage focuses on hemodynamic fluctuations and the impact of abdominal pressure changes on the circulatory system, and the postoperative stage focuses on changes in abdominal pressure and tissue perfusion recovery—identifying the patient's current stage through time points allows for the use of corresponding risk assessment parameters. Based on the identified stage, the corresponding parameter weighting is used. Different stages have different preset combinations of parameter weighting coefficients to reflect the degree of influence of various physiological changes on risk formation at that stage. For example, the preoperative stage primarily uses preoperative structural weighting coefficients and preoperative blood flow weighting coefficients; the intraoperative stage uses intraoperative blood flow weighting coefficients, intraoperative abdominal pressure weighting coefficients, and intraoperative perfusion weighting coefficients; and the postoperative stage uses postoperative abdominal pressure weighting coefficients and postoperative perfusion weighting coefficients. Based on the physiological change data corresponding to the current stage, and combined with the corresponding parameter weighting, a weighted fusion calculation is performed to obtain the current risk assessment parameters. The risk value for the previous stage is calculated as follows: Specifically, when the current stage is preoperative, the rate of change in tumor structure and the rate of change in hemodynamics are extracted and multiplied by the preoperative structural weight coefficient and the preoperative blood flow weight coefficient, respectively. The calculated results are then weighted and fused to obtain the preoperative risk value. When the current stage is intraoperative, the rate of change in hemodynamics, the rate of change in abdominal pressure, and the rate of change in perfusion are extracted and weighted by the intraoperative blood flow weight coefficient, the intraoperative abdominal pressure weight coefficient, and the intraoperative perfusion weight coefficient, respectively. The intraoperative risk value is obtained through fusion calculation. When the current stage is postoperative... The rate of change in abdominal pressure and the rate of change in perfusion were extracted and multiplied by the postoperative abdominal pressure weighting coefficient and the postoperative perfusion weighting coefficient, respectively. The calculation results were then fused to obtain the postoperative stage risk value. Multidimensional physiological change information was fused and calculated according to stage characteristics to obtain a stage risk value that reflects the patient's current risk status. Based on the patient's different stages before, during, and after surgery, the corresponding stage parameter weighting was called to conduct risk assessment, making the risk calculation more consistent with the physiological change characteristics of different stages, thereby improving the accuracy and relevance of the risk assessment results.

[0029] In a preferred embodiment, a stage baseline risk interval is established within the current stage. When the stage risk value remains stable over multiple consecutive collection periods, the statistical average of the current stage risk value is used as the new baseline risk value. The corresponding stage risk trigger threshold is then obtained based on the baseline risk value, including: S401. Identify the current stage based on the patient's current perioperative time point, and establish a stage baseline risk interval within the current stage; S402. Obtain a preset collection time interval, continuously obtain stage risk assessment values ​​according to the preset collection time interval, and form a stage risk value set according to the collection time sequence; S403. Compare the stage risk values ​​corresponding to two adjacent collection periods to obtain the risk value change range between each adjacent collection period. S404. When the change in risk value within multiple consecutive collection periods is less than the preset stable change range, the corresponding multiple consecutive collection periods are determined as the stage risk stabilization period. S405. Obtain all stage risk values ​​corresponding to the stable period of stage risk and form a stable period risk value set. S406. Obtain the stable cycle mean of the stable cycle risk value set based on all stage risk values ​​in the stable cycle risk value set, and mark the stable cycle mean as the benchmark risk value for the current stage. S407. Obtain the risk trigger threshold for the corresponding stage based on the benchmark risk value.

[0030] As described in steps S401 to S407 above, the current stage is identified based on the patient's current perioperative time point, and a baseline risk range is established within this stage. Specifically, an initial risk value range can be set for different stages based on historical perioperative monitoring data or preset medical experience parameters. The upper and lower limits of this range can be determined jointly by the initial risk trigger threshold and the safety margin. For example, a range can be formed by setting an upper and lower fluctuation ratio around the initial risk trigger threshold, thereby creating a baseline risk range for monitoring risk trends. This range is used to provide a reference range in the early stages of risk assessment to avoid single abnormal fluctuations affecting risk judgment. Interference is addressed by continuously acquiring stage risk assessment values ​​at preset collection time intervals, forming a stage risk value set according to the collection time sequence. The collection time interval can be set according to perioperative monitoring needs, such as every 1 minute, 5 minutes, or other fixed time periods, thereby achieving continuous monitoring of the patient's risk status. The stage risk values ​​corresponding to two adjacent collection cycles in the stage risk value set are compared, and the change in risk value between each adjacent collection cycle is calculated to obtain the degree of fluctuation of risk value over time. When the change in risk value in multiple consecutive collection cycles is less than the preset stable change range, it indicates that the patient's current physiological state is stable at that time. The period is relatively stable, therefore, multiple consecutive collection cycles are defined as the stage risk stabilization period. The stable range can be pre-set based on historical clinical monitoring data or system experience parameters. All stage risk values ​​within the stage risk stabilization period are obtained, forming a stable period risk value set. This risk value set reflects the patient's risk level in a stable state. Statistical processing is performed on all stage risk values ​​in the stable period risk value set; for example, all risk values ​​are first summed, then divided by the number of risk values ​​to obtain the average, thus obtaining the stable period mean. This stable period mean is marked as the baseline risk value for the current stage. Risk values ​​can objectively reflect a patient's stable risk status at the current stage. Based on the obtained baseline risk value, the corresponding risk trigger threshold is obtained. Specifically, a preset risk offset or proportional amplification can be added to the baseline risk value to generate the trigger threshold. For example, a final risk trigger threshold can be generated by setting a risk amplification coefficient or a safety offset. When the stage risk value exceeds the trigger threshold, it can be identified as a potential risk event. This realizes the construction of a dynamic baseline based on the stable status of real-time risk data, thereby forming a risk trigger mechanism that adapts to changes in the individual patient's status. This can more accurately identify abnormal risk changes and improve the accuracy of perioperative risk warning.

[0031] In a preferred embodiment, the risk trigger threshold for the corresponding stage is obtained based on a baseline risk value, including: S4071. Obtain the upper and lower boundary values ​​of the stage benchmark risk range; S4072. Based on the numerical distance between the benchmark risk value and the upper and lower boundary values ​​of the stage benchmark risk interval, obtain the threshold offset range of the preset initial risk trigger threshold for the current stage relative to the benchmark risk value. S4073. Based on the preset initial risk trigger threshold for the current stage, obtain the current offset position of the initial risk trigger threshold relative to the baseline risk value. S4074. When the current offset position is within the stage benchmark risk range, the initial risk trigger threshold is adjusted according to the threshold offset range, so that the adjusted initial risk trigger threshold is moved to a preset position outside the stage benchmark risk range, and the adjusted initial risk trigger threshold is marked as the risk trigger threshold of the current stage.

[0032] As described in steps S4071 to S4074 above, a reasonable risk range is set based on the patient's baseline risk value in the current stage. The upper and lower boundaries of the range can be referenced from historical risk data or medical experience. The upper boundary represents the maximum allowable normal range of the risk value in this stage, and the lower boundary represents the minimum normal range. This risk range is used to determine whether the initial risk trigger threshold is reasonable. The threshold offset range is used to determine the range of adjustment that the initial risk trigger threshold can make relative to the baseline risk value. The distance from the baseline risk value to the upper and lower boundaries of the risk range is calculated as the allowable offset range. The difference between the initial risk trigger threshold and the baseline risk value is used as the current initial offset. If the initial risk trigger threshold is within the risk range, adjustment is required; if it is outside the range, no adjustment is needed. The current offset position reflects the relative position of the initial risk trigger threshold and the baseline risk value. By determining where the initial threshold is located within the risk range, it can be determined whether threshold adjustment is required. If the initial threshold is within the baseline risk range, it indicates that the threshold is close to the patient's current stable risk level, which may easily lead to false alarms. Adjustment to move it outside the range is necessary. If the initial threshold is outside the range, it indicates that the threshold already has a certain safety buffer and no adjustment is needed. When the initial threshold is found to be within the baseline risk range, it is adjusted to a safe position outside the range based on the threshold offset range. The adjustment direction is determined, generally moving it upwards from the range so that the trigger threshold is slightly higher than the normal range of the baseline risk range. The adjustment range can refer to the offset range and the preset safety factor to ensure that the trigger threshold can identify abnormalities in a timely manner without causing false alarms due to normal fluctuations. After adjustment, the new threshold is used as the effective risk trigger threshold for the current stage for subsequent real-time risk monitoring and nursing prompts. This allows for the dynamic and intelligent generation of risk trigger thresholds for each stage, ensuring that the threshold matches the patient's actual condition while having a sufficient safety buffer. This ensures that risk monitoring is sensitive to real abnormalities but not to normal fluctuations, thereby reducing false alarms and missed alarms and improving the accuracy of perioperative nursing.

[0033] In a preferred implementation, when the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, a stage enhancement mode is executed to adjust the parameter weight reassembly corresponding to the current stage. When the risk value recovers to within the baseline risk range, the original parameter weight reassembly is restored, including: S501. Obtain the stage risk value set, compare the stage risk value corresponding to multiple consecutive collection cycles in the stage risk value set with the risk trigger threshold of the current stage, and determine that the current stage is in a risk over-threshold state when the stage risk value of multiple consecutive collection cycles is greater than the risk trigger threshold. S502. When the risk threshold is exceeded, the current stage enhancement mode is activated, and the parameter weights corresponding to the current stage are adjusted according to the preset weight adjustment rules. S503. Obtain the stage risk value according to the preset collection time interval, and determine whether the stage risk value enters the stage benchmark risk range. S504. When the stage risk value re-enters the stage benchmark risk range and maintains a preset stable period, the stage enhancement mode is terminated, and the original parameter weight reconfiguration preset for the current stage is restored.

[0034] As described in steps S501 to S504 above, the risk value of the current stage is continuously acquired and compared with the risk trigger threshold of the stage. If the risk value of multiple consecutive acquisition cycles is higher than the trigger threshold, the stage is determined to be in a risk over-threshold state, indicating that the patient's current state may be abnormal or the risk is increased, requiring timely response. When the risk over-threshold state is determined, the stage enhancement mode is entered. According to the preset weight adjustment rules, the parameter weighting of the current stage is dynamically adjusted. After adjustment, the weight of important physiological indicators (such as blood flow, abdominal pressure, or perfusion) is increased, making the risk value calculation more sensitive, thereby reflecting the patient's risk changes more quickly. Monitoring can be enhanced when the risk is increased to ensure that abnormal states are detected in time. During the operation of the enhancement mode, the risk value continues to be acquired according to the preset acquisition time interval, and it is determined whether the risk value has re-entered the stage baseline risk range to ensure continuous tracking of the patient's state, dynamic monitoring of risk changes, and avoidment of any important information. When the risk value re-enters the baseline risk range and remains stable for a period of time, the enhancement mode is automatically terminated and the original parameter weighting is restored, ensuring that the monitoring system is not oversensitive after the risk returns to normal, reducing false alarms, and maintaining normal monitoring efficiency.

[0035] In a preferred embodiment, a real-time risk level is obtained based on the current stage risk value and output to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold for the corresponding stage, a nursing prompt message is generated, including: S601. Obtain the real-time risk level for the corresponding collection period based on the current stage risk value; S602. The real-time risk level is sent to the nursing terminal through the monitoring system and displayed on the nursing terminal. S603. Obtain the stage risk trigger threshold corresponding to the current stage, and compare the real-time risk level with the stage risk trigger threshold. When the real-time risk level exceeds the stage risk trigger threshold, a corresponding nursing prompt message is generated and sent to the nursing terminal.

[0036] As described in steps S601 to S603 above, the risk value of each collection cycle is converted into a corresponding real-time risk level based on the risk value of the current stage. This reflects the patient's risk level at the current stage and real-time changes in physiological state. The real-time risk level is sent to the nursing terminal through the monitoring system and displayed on the terminal. Nurses can intuitively see the changes in the patient's risk level on the terminal without manually calculating or analyzing historical data. Through the visual display, nurses can quickly understand the patient's risk status, improve response efficiency, obtain the risk trigger threshold corresponding to the current stage, and compare the real-time risk level with this threshold. When the real-time risk level exceeds the risk trigger threshold, nursing prompts are automatically generated, such as indicating that the patient is at high risk and needs to pay attention to blood flow or perfusion status. The nursing prompts are sent to nurses through the nursing terminal to achieve timely intervention, ensuring that when the risk is higher than the safe range, nurses can take immediate measures to reduce the occurrence of potential complications.

[0037] Please see the appendix Figure 2 As shown, the present invention also provides a perioperative nursing system for abdominal aortic aneurysms, used in the above-mentioned perioperative nursing method for abdominal aortic aneurysms, comprising: The phase division module is used to divide the perioperative period into the preoperative phase, intraoperative phase and postoperative phase, and to preset the corresponding parameter weighting and initial risk triggering threshold for each phase. The physiological change module is used to continuously collect the patient's physiological data at preset time intervals during the perioperative period and obtain physiological change data based on the physiological data. The physiological change data includes the rate of change of tumor structure, the rate of change of hemodynamics, the rate of change of abdominal pressure, and the rate of change of perfusion. The stage risk module is used to obtain the risk value of the current stage based on the parameter weighting of the corresponding stage and the corresponding physiological change data. The trigger threshold module is used to establish a stage baseline risk range within the current stage. When the stage risk value remains stable within multiple consecutive collection cycles, the statistical mean of the current stage risk value is used as the new baseline risk value, and the risk trigger threshold for the corresponding stage is obtained based on the baseline risk value. The weight adjustment module is used to execute the stage enhancement mode when the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, and adjust the corresponding parameter weight reassembly in the current stage. When the risk value recovers to the baseline risk range, the original parameter weight reassembly is restored. The nursing alert module is used to obtain the real-time risk level based on the current stage risk value and output it to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold of the corresponding stage, a nursing alert message is generated.

[0038] The aforementioned stage division module divides the patient's perioperative period into three stages: preoperative, intraoperative, and postoperative, based on the surgical procedure timeline. Each stage has pre-set parameter weighting and initial risk trigger thresholds, enabling precise risk assessment based on the physiological characteristics and risk factors of each stage. By clearly defining the stages, the system can perform differentiated analysis and intervention for key physiological indicators at different stages. The physiological change module continuously collects multiple physiological data from the patient at preset time intervals, including tumor structure information, hemodynamic parameters, abdominal pressure, and perfusion-related indicators. Based on this data, it generates physiological change data such as tumor structure change rate, hemodynamic change rate, abdominal pressure change rate, and perfusion change rate. Through continuous monitoring and quantification of changes, the system can reflect the fluctuations in the patient's physiological state and potential risks in real time. The stage risk module calculates the stage risk value by combining the current stage's parameter weighting and physiological change data. Different stages use different weighting combinations based on their key risk factors; for example, preoperatively, the focus is on tumor structure and hemodynamics; intraoperatively, on hemodynamics, abdominal pressure, and perfusion; and postoperatively, on abdominal pressure and perfusion. The calculated risk value reflects the patient's overall risk level at the current stage, providing a basis for threshold judgment and... The intervention provides basic data and a trigger threshold module. This module establishes a baseline risk range for the current stage and determines the baseline risk value for the current stage by assessing the stability of risk values ​​across multiple consecutive data collection cycles. Based on this baseline risk value, the system adjusts and acquires the corresponding risk trigger threshold, dynamically adapting the threshold to the patient's physiological state and ensuring the accuracy of risk warnings. A weight adjustment module automatically activates a stage enhancement mode when the stage risk value continuously exceeds the trigger threshold, dynamically adjusting the corresponding parameter weights to strengthen risk monitoring. When the risk value returns to the baseline range and remains stable, the system restores the original weight combination, ensuring the accuracy and flexibility of risk monitoring and nursing interventions. A nursing prompt module generates a real-time risk level based on the current stage risk value and sends it to the nursing terminal for display. When the real-time risk level exceeds the stage trigger threshold, the system automatically generates a nursing prompt message to remind nursing staff to take timely intervention measures. This integrated approach to risk assessment, early warning, and nursing prompts ensures that nursing staff can respond to changes in the patient's condition in real time. It enables dynamic monitoring and intelligent early warning of the perioperative risk status of patients with abdominal aortic aneurysms, improving the timeliness and accuracy of nursing interventions and demonstrating significant clinical application value.

[0039] And, a perioperative care terminal for abdominal aortic aneurysm, comprising: One or more processors; A storage device on which one or more programs are stored; When one or more programs are executed by one or more processors, the one or more processors implement perioperative care methods for abdominal aortic aneurysms.

[0040] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A perioperative nursing method for abdominal aortic aneurysm, characterized in that, include: The perioperative period is divided into the preoperative stage, the intraoperative stage and the postoperative stage, and corresponding parameter weighting and initial risk triggering thresholds are preset for each stage. Physiological data of patients are continuously collected at preset time intervals during the perioperative period. Physiological change data are obtained based on the physiological data, including the rate of change of tumor structure, the rate of change of hemodynamics, the rate of change of abdominal pressure, and the rate of change of perfusion. Within the current stage, the risk value of the current stage is obtained by recombining the parameter weights of the corresponding stage and combining them with the corresponding physiological change data. Establish a stage benchmark risk range within the current stage. When the stage risk value remains stable over multiple consecutive collection periods, use the statistical mean of the current stage risk value as the new benchmark risk value, and obtain the corresponding stage risk trigger threshold based on the benchmark risk value. When the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, the stage enhancement mode is executed, the corresponding parameter weight reassembly in the current stage is adjusted, and the original parameter weight reassembly is restored when the risk value returns to the baseline risk range. The real-time risk level is obtained based on the current stage risk value and output to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold of the corresponding stage, a nursing prompt message is generated.

2. The perioperative nursing method for abdominal aortic aneurysm according to claim 1, characterized in that, The perioperative period is divided into preoperative, intraoperative, and postoperative stages, and corresponding parameter weighting and initial risk trigger thresholds are preset for each stage, including: Based on the surgical procedure timeline, the patient management process is divided into the preoperative stage, the intraoperative stage, and the postoperative stage. The preoperative stage is the time interval from when the patient enters the surgical preparation state to before the start of the surgery; the intraoperative stage is the time interval from the start of the surgery to the end of the surgery; and the postoperative stage is the time interval from the end of the surgery to the termination of perioperative monitoring. In the preoperative stage, preoperative parameter weighting is preset, and preoperative initial risk triggering threshold is preset. The preoperative parameter weighting includes preoperative structural weighting coefficient, preoperative blood flow weighting coefficient, preoperative abdominal pressure weighting coefficient, and preoperative perfusion weighting coefficient. During the intraoperative phase, intraoperative parameter weighting is preset, and intraoperative initial risk triggering threshold is preset. The intraoperative parameter weighting includes intraoperative structural weighting coefficient, intraoperative blood flow weighting coefficient, intraoperative abdominal pressure weighting coefficient, and intraoperative perfusion weighting coefficient. In the postoperative stage, the postoperative parameter weighting is preset, and the initial postoperative risk trigger threshold is preset. The postoperative parameter weighting includes the postoperative structural weighting coefficient, the postoperative blood flow weighting coefficient, the postoperative abdominal pressure weighting coefficient, and the postoperative perfusion weighting coefficient.

3. The perioperative nursing method for abdominal aortic aneurysm according to claim 1, characterized in that, Physiological data of patients were continuously collected at preset time intervals during the perioperative period. Physiological change data were obtained based on the physiological data, including the rate of change in tumor structure, the rate of change in hemodynamics, the rate of change in abdominal pressure, and the rate of change in perfusion, including: During the perioperative period, physiological data of patients were continuously collected at preset collection time intervals. The physiological data included the maximum diameter of the tumor, the thickness of the tumor wall, systolic blood pressure, diastolic blood pressure, heart rate, intra-abdominal pressure, mean arterial pressure, urine output, and blood lactate. Based on the maximum diameter and wall thickness data of the tumor, the corresponding change values ​​and directions are obtained, and the tumor structure change rate is generated. Based on systolic blood pressure data, diastolic blood pressure data, and heart rate data, obtain the corresponding change values ​​and directions of change, and generate the hemodynamic change rate; Based on the intra-abdominal pressure data, the corresponding change value and direction of change are obtained, and the rate of change of intra-abdominal pressure is generated. Based on mean arterial pressure data, urine output data, and blood lactate data, obtain the corresponding change values ​​and directions, and generate the perfusion change rate; Physiological change data were generated by summarizing the rates of change in tumor structure, hemodynamics, abdominal pressure, and perfusion.

4. The perioperative nursing method for abdominal aortic aneurysm according to claim 1, characterized in that, Within the current stage, the risk value for the current stage is obtained based on the parameter weighting of the corresponding stage and in conjunction with the corresponding physiological change data, including: Identify the current stage based on the patient's current perioperative timeline; Obtain the corresponding parameter weights and reorganize them according to the current stage; Based on the physiological data corresponding to the current stage, and combined with the corresponding parameter weighting, the risk value for the current stage is obtained; If the current stage is the preoperative stage, the preoperative structural weight coefficient and preoperative blood flow weight coefficient are obtained from the corresponding parameter weight recombination, and the tumor structure change rate and hemodynamic change rate are extracted according to the corresponding physiological data, and weighted fusion is performed to obtain the preoperative stage risk value. If the current stage is the intraoperative stage, the intraoperative blood flow weight coefficient, intraoperative abdominal pressure weight coefficient and intraoperative perfusion weight coefficient are obtained from the corresponding parameter weighting recombination. Based on the corresponding physiological data, the hemodynamic change rate, abdominal pressure change rate and perfusion change rate are extracted and weighted to obtain the intraoperative stage risk value. If the current stage is the postoperative stage, the postoperative abdominal pressure weight coefficient and postoperative perfusion weight coefficient are obtained from the corresponding parameter weighting reassembly, and the abdominal pressure change rate and perfusion change rate are extracted based on the corresponding physiological data, and weighted fusion is performed to obtain the postoperative stage risk value.

5. The perioperative nursing method for abdominal aortic aneurysm according to claim 1, characterized in that, Establish a baseline risk range for the current phase. When the phase risk value remains stable over multiple consecutive data collection periods, use the statistical mean of the current phase risk value as the new baseline risk value. Based on this baseline risk value, obtain the corresponding risk trigger threshold for the phase, including: Identify the current stage based on the patient's current perioperative time point, and establish a stage baseline risk interval within the current stage; Obtain a preset data collection time interval, continuously acquire stage risk assessment values ​​according to the preset data collection time interval, and form a stage risk value set in the order of data collection time; Compare the stage risk values ​​corresponding to two adjacent collection periods in the stage risk value set to obtain the risk value change range between each adjacent collection period. When the change in risk value within multiple consecutive collection periods is less than the preset stable change range, the corresponding multiple consecutive collection periods are determined as the stage risk stabilization period. Obtain all stage risk values ​​corresponding to the stable period of stage risk, and form a stable period risk value set; The stable cycle mean of the stable cycle risk value set is obtained from all the stage risk values ​​in the stable cycle risk value set, and the stable cycle mean is marked as the benchmark risk value for the current stage. Obtain the risk trigger threshold for the corresponding stage based on the benchmark risk value.

6. The perioperative nursing method for abdominal aortic aneurysm according to claim 5, characterized in that, The risk trigger thresholds for the corresponding stage are obtained based on the benchmark risk value, including: Obtain the upper and lower boundary values ​​of the stage benchmark risk range; Based on the numerical distance between the benchmark risk value and the upper and lower boundary values ​​of the stage benchmark risk interval, the threshold offset range of the preset initial risk trigger threshold for the current stage relative to the benchmark risk value is obtained. Based on the preset initial risk trigger threshold for the current stage, obtain the current offset position of the initial risk trigger threshold relative to the baseline risk value; When the current offset position is within the stage baseline risk range, the initial risk trigger threshold is adjusted according to the threshold offset range, so that the adjusted initial risk trigger threshold is moved to a preset position outside the stage baseline risk range, and the adjusted initial risk trigger threshold is marked as the risk trigger threshold of the current stage.

7. The perioperative nursing method for abdominal aortic aneurysm according to claim 1, characterized in that, When the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, the stage enhancement mode is executed, and the parameter weights corresponding to the current stage are adjusted. When the risk value recovers to the baseline risk range, the original parameter weights are restored, including: Obtain the stage risk value set, compare the stage risk value corresponding to multiple consecutive collection periods in the stage risk value set with the risk trigger threshold of the current stage, and determine that the current stage is in a risk over-threshold state when the stage risk value of multiple consecutive collection periods is greater than the risk trigger threshold. When the risk threshold is exceeded, the current stage enhancement mode is activated, and the parameter weights corresponding to the current stage are adjusted according to the preset weight adjustment rules. The stage risk value is obtained according to the preset collection time interval, and it is determined whether the stage risk value has entered the stage benchmark risk range. When the stage risk value re-enters the stage benchmark risk range and maintains a preset stable period, the stage enhancement mode is terminated, and the original parameter weights preset for the current stage are restored.

8. The perioperative nursing method for abdominal aortic aneurysm according to claim 1, characterized in that, The real-time risk level is obtained based on the current stage risk value and output to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold for the corresponding stage, a nursing prompt message is generated, including: Obtain the real-time risk level for the corresponding data collection period based on the current stage risk value; The real-time risk level is sent to the nursing terminal through the monitoring system and displayed on the nursing terminal; Obtain the stage risk trigger threshold corresponding to the current stage, and compare the real-time risk level with the stage risk trigger threshold; When the real-time risk level exceeds the stage risk trigger threshold, a corresponding nursing prompt message is generated and sent to the nursing terminal.

9. A perioperative nursing system for abdominal aortic aneurysm, applied to the perioperative nursing method for abdominal aortic aneurysm as described in any one of claims 1 to 8, characterized in that, include: The phase division module is used to divide the perioperative period into the preoperative phase, intraoperative phase and postoperative phase, and to preset the corresponding parameter weighting and initial risk triggering threshold for each phase. The physiological change module is used to continuously collect the patient's physiological data at preset time intervals during the perioperative period and obtain physiological change data based on the physiological data. The physiological change data includes the rate of change of tumor structure, the rate of change of hemodynamics, the rate of change of abdominal pressure, and the rate of change of perfusion. The stage risk module is used to obtain the risk value of the current stage based on the parameter weighting of the corresponding stage and the corresponding physiological change data. The trigger threshold module is used to establish a stage baseline risk range within the current stage. When the stage risk value remains stable within multiple consecutive collection cycles, the statistical mean of the current stage risk value is used as the new baseline risk value, and the risk trigger threshold for the corresponding stage is obtained based on the baseline risk value. The weight adjustment module is used to execute the stage enhancement mode when the risk value of the current stage exceeds the risk trigger threshold of the corresponding stage for multiple consecutive collection cycles, and adjust the corresponding parameter weight reassembly in the current stage. When the risk value recovers to the baseline risk range, the original parameter weight reassembly is restored. The nursing alert module is used to obtain the real-time risk level based on the current stage risk value and output it to the nursing terminal. When the real-time risk level exceeds the risk trigger threshold of the corresponding stage, a nursing alert message is generated.

10. A perioperative nursing terminal for abdominal aortic aneurysm, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When one or more programs are executed by one or more processors, the one or more processors implement the perioperative care method for abdominal aortic aneurysm as described in any one of claims 1 to 8.

Images