A method and system for monitoring and processing post-thoraco-abdominal leakage drainage fluid

Abstract

The application discloses a kind of postoperative thoracoabdominal leakage drainage fluid monitoring processing method and system, it is related to drainage fluid monitoring technical field, its technical solution key points include the following steps: obtaining the postoperative basic information of target patient and drainage fluid monitoring data;According to postoperative basic information, determine corresponding drainage evaluation standard;Wherein, the drainage evaluation standard includes multiple drainage standard factors and standard parameter interval;According to drainage fluid monitoring data, at least one drainage monitoring factor and corresponding monitoring parameter are extracted;According to abnormal monitoring factor and corresponding monitoring parameter, generate the drainage evaluation state feature of target patient;According to drainage evaluation state feature and preset abnormal processing library, output the drainage processing scheme of target patient, effect is to improve the efficiency and response speed of postoperative drainage management.

Description

Technical Field

[0001] This invention relates to the field of drainage fluid monitoring technology, and more specifically, to a method and system for monitoring and managing drainage fluid after thoracic or abdominal fistula surgery. Background Technology

[0002] Postoperative drainage monitoring after pleural and abdominal fistula surgery is a core component in ensuring postoperative recovery and preventing complications such as bleeding and infection. However, traditional monitoring methods mainly rely on medical staff manually observing the color and characteristics of the drainage fluid and estimating the drainage volume. The data collection dimensions are singular, lacking hierarchical analysis and in-depth interpretation of dynamic and static characteristic data. Focusing on single flow indicators such as drainage volume, it fails to combine the inherent properties of the drainage fluid such as pH value, protein content, and turbidity for comprehensive analysis, and also fails to capture the dynamic characteristics of the drainage volume fluctuation amplitude and rate of change over time. This results in incomplete extraction of monitoring factors, failing to fully reflect the true state of the drainage fluid and the healing process of the patient's wound. In addition, after abnormality identification, there is a lack of dynamic analysis of the duration and fluctuation pattern of the abnormality, making it impossible to distinguish between instantaneous fluctuation abnormalities and persistent pathological abnormalities. This makes the abnormality assessment lack a sense of hierarchy and difficult to guide subsequent targeted interventions. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method and system for monitoring and treating postoperative drainage fluid in patients with thoracic and abdominal leaks.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery includes the following steps: Obtain postoperative basic information and drainage fluid monitoring data of the target patients; The corresponding drainage assessment criteria are determined based on postoperative baseline information; wherein, the drainage assessment criteria include multiple drainage standard factors and standard parameter ranges; At least one drainage monitoring factor and its corresponding monitoring parameters were extracted from the drainage fluid monitoring data. After matching the traffic monitoring factors with the traffic standard factors, the judgment result is obtained by determining whether the monitoring parameters exceed the corresponding standard parameter range. Based on the judgment results, the corresponding drainage monitoring factors are identified as abnormal monitoring factors; Generate the drainage assessment status characteristics of the target patient based on abnormal monitoring factors and corresponding monitoring parameters; Based on the characteristics of the drainage assessment and the pre-set abnormality handling library, the drainage treatment plan for the target patient is output.

[0005] Preferably, the corresponding drainage assessment criteria are determined based on postoperative baseline information, specifically including the following steps: Attribute information is obtained by classifying attributes from multiple dimensions based on postoperative baseline information; Based on the physiological tolerance characteristics and attribute information of drainage, suitable drainage standard factors were selected. The standard parameter range is obtained by matching the differential parameter range corresponding to the standard drainage factor based on the degree of wound leakage. The standard factors and standard parameter ranges for attracting traffic constitute the criteria for evaluating traffic.

[0006] Preferably, at least one drainage monitoring factor and its corresponding monitoring parameters are extracted from the drainage fluid monitoring data, specifically including the following steps: The drainage fluid monitoring data were stratified and analyzed to obtain dynamic change data and static characteristic data; Based on physiological correlation characteristics, dynamic change data and static feature data are decomposed in a targeted manner to obtain data representation dimensions, and the extraction direction of drainage monitoring factors is determined according to the data representation dimensions. Based on the extraction direction, dynamic change data and static feature data are extracted to obtain the flow monitoring factor; The monitoring parameters are obtained by collecting data characterization information corresponding to the drainage monitoring factors.

[0007] Preferably, the flow monitoring factors are obtained by extracting dynamic change data and static feature data according to the extraction direction, specifically including the following steps: Based on the extraction direction, the first correlation factor reflecting the real-time fluctuation of the drainage fluid is extracted from the dynamically changing data. Based on the extraction direction, a second relevant factor reflecting the inherent properties of the drainage fluid is extracted from static feature data; The first and second relevant factors are integrated to form the drainage monitoring factor.

[0008] Preferably, after matching the drainage monitoring factors with the drainage standard factors, the judgment result is obtained by determining whether the monitoring parameters exceed the corresponding standard parameter range. This specifically includes the following steps: Identify the correlation between traffic acquisition monitoring factors, and obtain factor groups by matching traffic acquisition standard factors based on the correlation; Extract the standard parameter range corresponding to the factor group; The judgment result is obtained by determining whether the monitoring parameters corresponding to the drainage monitoring factors exceed the corresponding standard parameter range.

[0009] Preferably, the corresponding drainage monitoring factor is identified as an abnormal monitoring factor based on the judgment result, specifically including the following steps: If the monitoring parameter corresponding to the drainage monitoring factor exceeds the standard parameter range and the first comparison result is obtained, the corresponding drainage monitoring factor will be marked as an abnormal correlation factor. If the monitoring parameters corresponding to the drainage monitoring factors do not exceed the standard parameter range and a second comparison result is obtained, then the correlation and coordination between the monitoring parameters are judged. If the correlation and coordination between the monitoring parameters shows an abnormal tendency and a third comparison result is obtained, the corresponding diversion monitoring factor will be marked as an abnormal correlation factor. The first comparison result, the second comparison result, and the third comparison result are combined to form the judgment result.

[0010] Preferably, the process of generating drainage assessment status characteristics of the target patient based on abnormal monitoring factors and corresponding monitoring parameters specifically includes the following steps: The duration of anomalies of the anomaly monitoring factors is obtained based on the anomaly monitoring factors and their corresponding monitoring parameters; The instantaneous anomaly factor and the continuous anomaly factor are obtained based on the duration of the anomaly and the changing trend of the corresponding monitoring parameters. Integrating the peak deviation and duration of the monitoring parameters corresponding to the transient anomaly factors yields the transient anomaly characteristics; Determine the fluctuation pattern of the monitoring parameters corresponding to the persistent abnormal factors, and obtain the persistent abnormal characteristics of the abnormal monitoring factors based on the fluctuation pattern; By associating and integrating transient abnormal features with persistent abnormal features, the drainage assessment status characteristics of the target patient are obtained.

[0011] Preferably, the transient anomaly factor is a factor that recovers automatically after the monitored parameter deviates from the standard parameter range; The persistent abnormal factor is the factor whose monitored parameter deviates from the standard parameter range and shows no recovery trend.

[0012] A system for monitoring and managing postoperative drainage fluid from pleural and abdominal fistulas includes: Acquisition module: Acquires postoperative basic information and drainage fluid monitoring data of the target patient; Processing module: Determines the corresponding drainage assessment criteria based on postoperative baseline information; wherein, the drainage assessment criteria include multiple drainage standard factors and standard parameter ranges; Extraction module: Extracts at least one drainage monitoring factor and its corresponding monitoring parameters based on the drainage fluid monitoring data; Judgment module: After matching the traffic monitoring factors with the traffic standard factors, it determines whether the monitoring parameters exceed the corresponding standard parameter range to obtain the judgment result; Determination Module: Based on the judgment results, the corresponding traffic monitoring factors are determined as abnormal monitoring factors; Generation module: Generates the drainage assessment status characteristics of the target patient based on abnormal monitoring factors and corresponding monitoring parameters; Output module: Outputs the drainage treatment plan for the target patient based on the drainage assessment status characteristics and the preset abnormality handling library.

[0013] Compared with the prior art, the present invention has the following beneficial effects: This invention, based on patients' postoperative baseline information, constructs a drainage assessment standard encompassing multiple drainage standard factors and differentiated parameter ranges. Through hierarchical analysis of drainage fluid monitoring data, it extracts dynamic change data and static characteristic data, forming a complete drainage monitoring factor system that includes real-time fluctuations and inherent attributes. This system covers both dynamic information such as changes in drainage volume and drainage speed fluctuations, and static information such as the physicochemical properties of drainage fluid, providing a more comprehensive monitoring dimension. By distinguishing between transient and persistent abnormal factors, it extracts drainage assessment status characteristics including deviations from peak values, duration, and fluctuation patterns, achieving graded and refined characterization of abnormal states and providing a basis for subsequent treatment plan formulation. Through intelligent matching of a pre-set abnormal treatment database with patient status characteristics, it achieves automated output of drainage treatment plans, ensuring both standardization and normalization of treatment measures while providing targeted intervention guidance based on individual patient conditions. This significantly shortens the time for medical staff to assess and formulate plans, improves the efficiency and response speed of postoperative drainage management, and provides technical assurance for the drainage safety and recovery of patients after thoracic and abdominal fistula surgery. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating a method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery, as provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of a module for monitoring and processing postoperative drainage fluid after thoracic or abdominal leakage, provided in an embodiment of the present invention. Detailed Implementation

[0015] 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.

[0016] 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.

[0017] 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 one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0018] Reference Figures 1-2 As shown.

[0019] The embodiments further illustrate the method and system for monitoring and treating postoperative drainage fluid in thoracic and abdominal fistulas proposed in this invention.

[0020] A method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery includes the following steps: Obtain postoperative basic information and drainage fluid monitoring data of the target patients; The corresponding drainage assessment criteria are determined based on postoperative baseline information; these criteria include multiple drainage standard factors and standard parameter ranges; specifically, the following steps are included: Attribute information is obtained by classifying attributes from multiple dimensions based on postoperative baseline information; Based on the physiological tolerance characteristics and attribute information of drainage, suitable drainage standard factors were selected. The standard parameter range is obtained by matching the differential parameter range corresponding to the standard drainage factor based on the degree of wound leakage. The standard factors and standard parameter ranges for attracting traffic constitute the criteria for evaluating traffic.

[0021] The postoperative basic information of the target patients is classified into multiple dimensions. The postoperative basic information includes physiological information, surgery-related information, and health information. Physiological information includes the patient's age, weight, and gender. Surgery-related information includes the type of surgery and the location of the incision. Health information includes whether there are underlying diseases and the postoperative recovery time. These scattered pieces of information are sorted and integrated according to different dimensions to obtain structured attribute information. For example, the patient's age is classified as a physiological attribute dimension, the presence of diabetes is classified as an underlying disease dimension, and the location of the surgical incision is classified as a surgery-related dimension. Through this classification, the originally scattered information is organized into orderly attribute information.

[0022] By combining drainage physiological tolerance characteristics and attribute information, suitable drainage standard factors are screened. Drainage physiological tolerance characteristics refer to the body's routine tolerance to drainage-related indicators in different populations after thoracic and abdominal fistula surgery. For example, the tolerance of healthy young and middle-aged patients to the total amount of drainage fluid is significantly different from that of elderly patients with hypoalbuminemia. By matching attribute information with drainage physiological tolerance characteristics, indicators related to the individual patient's condition are screened as drainage standard factors. When the patient's attribute information shows that they have hypoalbuminemia, the indicator of drainage fluid protein content is included in the suitable drainage standard factors, while general indicators that are not related to the patient's physical condition are excluded, ensuring that the screened factors are consistent with the patient's actual physiological state.

[0023] Based on the degree of wound leakage, differentiated parameter limits are matched to the standard factors for drainage, resulting in corresponding standard parameter ranges. The degree of wound leakage is quantified through a grading system, for example, divided into Level 1 (minor leakage), Level 2 (moderate leakage), and Level 3 (severe leakage). Different leakage degrees correspond to different parameter limits. Taking the daily drainage volume as an example, when the wound leakage degree is Level 1, it indicates good wound healing and low leakage. In this case, the lower limit of the standard parameter range for daily drainage volume is 100 ml, and the upper limit is 300 ml, meaning the reasonable range for daily drainage volume is 100 ml to 300 ml. When the wound leakage degree is Level 2, the leakage volume increases. In this case, the lower limit of the standard parameter range for daily drainage volume is 200 ml, and the upper limit is 500 ml, meaning the reasonable range for daily drainage volume is 200 ml to 500 ml. When the wound leakage level is grade 3, the leakage is relatively large. In this case, the lower limit of the standard parameter range for daily drainage volume is 300 ml, and the upper limit is 800 ml. Therefore, the reasonable range for daily drainage volume is 300 ml to 800 ml. This method matches a parameter range appropriate to the degree of wound leakage for each drainage standard factor, avoiding judgment errors caused by generic parameter ranges for patients in different recovery stages.

[0024] The standard factors for drainage and the standard parameter ranges corresponding to each factor are integrated to form a complete drainage assessment standard. Each standard factor for drainage corresponds to a suitable standard parameter range, and the set of all factors and ranges forms the drainage assessment standard for the target patient.

[0025] At least one drainage monitoring factor and its corresponding monitoring parameters are extracted from the drainage fluid monitoring data, specifically including the following steps: The drainage fluid monitoring data were stratified and analyzed to obtain dynamic change data and static characteristic data; Based on physiological correlation characteristics, dynamic change data and static feature data are decomposed in a targeted manner to obtain data representation dimensions, and the extraction direction of drainage monitoring factors is determined according to the data representation dimensions. Based on the extraction direction, dynamic change data and static feature data are extracted to obtain the traffic monitoring factors, specifically including the following steps: Based on the extraction direction, the first correlation factor reflecting the real-time fluctuation of the drainage fluid is extracted from the dynamically changing data. Based on the extraction direction, a second relevant factor reflecting the inherent properties of the drainage fluid is extracted from static feature data; The first and second relevant factors are integrated to form the drainage monitoring factor; The monitoring parameters are obtained by collecting data characterization information corresponding to the drainage monitoring factors; The drainage fluid monitoring data is divided into dynamic change data and static characteristic data. Dynamic change data is monitoring information that fluctuates in real time over time, such as the drainage volume per hour after the operation, the drainage fluid outflow rate, and the color of the drainage fluid changing over time. This type of data changes continuously with the patient's recovery status and drainage process. Static characteristic data refers to the inherent properties of the drainage fluid that do not change frequently in a short period of time, such as the initial color, initial turbidity, initial pH value, and initial protein content of the drainage fluid. This type of data mainly reflects the basic physicochemical characteristics of the drainage fluid.

[0026] Based on physiological correlation characteristics, dynamic and static feature data are decomposed separately to obtain data representation dimensions. These dimensions then determine the extraction direction of drainage monitoring factors. Physiological correlation characteristics refer to the inherent logical relationship between drainage fluid data and physiological indicators such as postoperative recovery, wound condition, and infection risk. For example, in dynamic data, the variation in drainage volume is directly related to the degree of wound leakage, and the fluctuation in drainage rate is related to the patency of the drainage tube. In static data, the turbidity of the drainage fluid is related to tissue exudation, and the pH value of the drainage fluid is related to the infection risk. Based on this characteristic, dynamic data is decomposed to obtain data representation dimensions such as time, variation amplitude, and variation rate, including hourly variations in drainage volume, daily variation rates of drainage volume, and fluctuations in drainage fluid outflow rate. Static feature data is decomposed to obtain data representation dimensions such as physicochemical properties and composition, including the color grade, turbidity grade, pH range, and protein content level of the drainage fluid. Based on these data representation dimensions, the extraction direction of drainage monitoring factors is determined. The extraction direction of dynamic change data focuses on indicators related to real-time fluctuations of drainage fluid, while the extraction direction of static feature data focuses on indicators related to the inherent properties of drainage fluid.

[0027] Based on the extraction direction, dynamic change data and static feature data are extracted separately and then integrated to form a complete drainage monitoring factor. From the dynamic change data, the first relevant factor reflecting the real-time fluctuation of drainage fluid is extracted. For example, based on the dynamic data of drainage volume, the hourly average drainage volume, the daily rate of change of drainage volume, and the fluctuation value of drainage fluid outflow velocity are extracted. Taking the hourly average drainage volume as an example, the hourly average drainage volume = the total drainage volume over 24 hours / 24, directly reflecting the average fluctuation level of drainage volume; the daily rate of change of drainage volume = the drainage volume of the current day - the drainage volume of the previous day, reflecting the daily variation range of drainage volume.

[0028] Secondary relevant factors reflecting the inherent properties of the drainage fluid are extracted from static feature data, such as the initial color grade, initial pH value, and initial protein content. For example, if the initial color of the drainage fluid is light red, then the corresponding color grade is set to 1, the initial pH value to 7.2, and the initial protein content to 20 g / L. These indicators directly reflect the basic physicochemical state of the drainage fluid. The primary and secondary relevant factors are integrated to form a complete drainage monitoring factor, which includes real-time dynamic information and inherent static information of the drainage fluid, comprehensively covering the key monitoring dimensions of the drainage status.

[0029] Data characterization information corresponding to drainage monitoring factors is collected to obtain monitoring parameters, that is, a specific quantitative value is assigned to each drainage monitoring factor. For example, the monitoring parameter for the hourly average drainage volume is 15 ml / hour, the monitoring parameter for the daily change rate of drainage volume is 50 ml, the monitoring parameter for the color grade of drainage fluid is 1, the monitoring parameter for the pH value of drainage fluid is 7.2, and the monitoring parameter for the protein content of drainage fluid is 20 g / L. If the units of different monitoring parameters are not consistent, unit conversion is required to achieve consistency. For example, the unit of the daily change rate of drainage volume is ml / day, and the unit of the hourly average drainage volume is ml / hour. The daily change rate of drainage volume is converted to ml / hour. The value of the daily change rate of drainage volume per hour = the daily change rate of drainage volume / 24. For example, the daily change rate of drainage volume is 50 ml / day, which is approximately 2.08 ml / hour after conversion.

[0030] After matching the traffic diversion monitoring factors with the traffic diversion standard factors, the judgment result is obtained by determining whether the monitoring parameters exceed the corresponding standard parameter range. The specific steps include: Identify the correlation between traffic acquisition monitoring factors, and obtain factor groups by matching traffic acquisition standard factors based on the correlation; Extract the standard parameter range corresponding to the factor group; The judgment result is obtained by determining whether the monitoring parameters corresponding to the diversion monitoring factors exceed the corresponding standard parameter range; The correlations between drainage monitoring factors are identified, and factor groups are obtained by matching drainage standard factors based on these correlations. Drainage monitoring factors are not independent of each other but rather exhibit inherent physiological relationships. For example, there are correlations between drainage volume and drainage fluid protein content, drainage fluid turbidity and infection risk, and drainage rate and drainage tube patency. Based on these correlations, related drainage monitoring factors are grouped into the same correlation group, and then the drainage monitoring factors within each correlation group are matched with drainage standard factors in the drainage assessment criteria to form factor groups.

[0031] For example, the drainage volume factor, the drainage fluid protein content factor, and the drainage fluid turbidity factor constitute a correlation factor group, which corresponds to the same type of drainage standard factor in the drainage evaluation standard, thus forming a correlation factor group between drainage volume and protein content, as well as a correlation factor group between drainage fluid turbidity, etc.

[0032] Each factor group's drainage standard factor is pre-configured with standard parameter ranges adapted to individual patient conditions. The corresponding standard parameter ranges are retrieved for each factor group. For example, in the drainage volume and protein content-related factor group, the standard parameter range for drainage volume is 100 ml to 300 ml per day, and the standard parameter range for drainage fluid protein content is 15 g / L to 30 g / L; in the drainage fluid turbidity-related factor group, the standard parameter range for turbidity level is grade 1 to 3. These parameter ranges are then linked to the factor groups.

[0033] The judgment result is obtained by determining whether the monitoring parameters corresponding to the drainage monitoring factors exceed the corresponding standard parameter range. The monitoring parameters of the drainage monitoring factors within each factor group are compared with the corresponding standard parameter range for that factor group. If the monitoring parameter is within the standard parameter range, it is considered normal; if the monitoring parameter is below the lower limit or above the upper limit of the standard parameter range, it is considered outside the standard parameter range. For example, if the monitoring parameter for drainage volume is 350 ml / day, and its standard parameter range is 100 ml / day to 300 ml / day, then the monitoring parameter for drainage volume is above the upper limit of the standard parameter range and is considered outside the standard parameter range. Similarly, if the monitoring parameter for drainage fluid protein content is 25 g / L, and its standard parameter range is 15 g / L to 30 g / L, then the monitoring parameter for drainage fluid protein content is within the standard parameter range and is considered within the standard parameter range. The judgment result is obtained by summarizing the comparison results of all factor groups.

[0034] Based on the judgment results, the corresponding drainage monitoring factors are identified as abnormal monitoring factors, specifically including the following steps: If the monitoring parameter corresponding to the drainage monitoring factor exceeds the standard parameter range and the first comparison result is obtained, the corresponding drainage monitoring factor will be marked as an abnormal correlation factor. If the monitoring parameters corresponding to the drainage monitoring factors do not exceed the standard parameter range and a second comparison result is obtained, then the correlation and coordination between the monitoring parameters are judged. If the correlation and coordination between the monitoring parameters shows an abnormal tendency and a third comparison result is obtained, the corresponding diversion monitoring factor will be marked as an abnormal correlation factor. The combination of the first comparison result, the second comparison result, and the third comparison result constitutes the judgment result. If the monitoring parameter corresponding to a drainage monitoring factor exceeds the standard parameter range and the first comparison result is obtained, then the corresponding drainage monitoring factor is directly marked as an abnormal correlation factor. For example, if the monitoring parameter for drainage volume is 400 ml per day, while its standard parameter range is 100 ml to 300 ml per day, then the monitoring parameter for drainage volume is higher than the upper limit of the standard parameter range, thus obtaining the first comparison result, and the drainage volume factor is directly marked as an abnormal correlation factor. Similarly, if the monitoring parameter for drainage fluid protein content is 35 g / L, while its standard parameter range is 15 g / L to 30 g / L, then the monitoring parameter for drainage fluid protein content is higher than the upper limit of the standard parameter range, thus obtaining the first comparison result, and the drainage fluid protein content factor is marked as an abnormal correlation factor.

[0035] If the monitoring parameters corresponding to the drainage monitoring factors do not exceed the standard parameter range, and a second comparison result is obtained, the correlation and coordination between the monitoring parameters should be determined. Correlation and coordination refer to whether the monitoring parameters of different drainage monitoring factors conform to normal physiological linkage patterns. For example, there is usually a positive correlation between drainage volume and drainage fluid protein content; as drainage volume increases, drainage fluid protein content also increases. If the trends of the two show a significant divergence, it indicates an abnormal tendency in correlation and coordination. For instance, if the monitoring parameter for drainage volume is 250 ml per day, falling within its standard parameter range of 100 ml to 300 ml per day, and the monitoring parameter for drainage fluid protein content is 18 g / L, falling within its standard parameter range of 15 g / L to 30 g / L, then both monitoring parameters do not exceed the standard parameter range, resulting in a second comparison result. Further assessment of the correlation and coordination between the two is needed. Under normal circumstances, when the drainage volume increases from 150 ml / day to 250 ml / day, the protein content of the drainage fluid should increase from 16 g / L to about 20 g / L. However, the actual monitoring parameter for the protein content of the drainage fluid is 18 g / L, which does not match the expected trend of correlation. At this point, it is determined that there is an abnormal tendency in the correlation and coordination between the monitoring parameters, thus obtaining the third comparison result. The drainage volume factor and the drainage fluid protein content factor are marked as abnormal correlation factors.

[0036] The first comparison result, the second comparison result, and the third comparison result are combined to form the final judgment result. The first comparison result corresponds to the explicit parameter over-limit anomaly, the third comparison result corresponds to the implicit correlation coordination anomaly, and the second comparison result is the transition judgment of the normal parameter state.

[0037] The drainage assessment status characteristics of the target patient are generated based on abnormal monitoring factors and corresponding monitoring parameters, specifically including the following steps: The duration of anomalies of the anomaly monitoring factors is obtained based on the anomaly monitoring factors and their corresponding monitoring parameters; The instantaneous anomaly factor and the continuous anomaly factor are obtained based on the duration of the anomaly and the changing trend of the corresponding monitoring parameters. Integrating the peak deviation and duration of the monitoring parameters corresponding to the transient anomaly factors yields the transient anomaly characteristics; Determine the fluctuation pattern of the monitoring parameters corresponding to the persistent abnormal factors, and obtain the persistent abnormal characteristics of the abnormal monitoring factors based on the fluctuation pattern; By associating and integrating transient abnormal features with persistent abnormal features, the drainage assessment status characteristics of the target patient are obtained.

[0038] Transient anomaly factors are those that recover spontaneously after the monitored parameters deviate from the standard parameter range; Persistent abnormal factors are those whose monitored parameters deviate from the standard parameter range and show no recovery trend; The duration of anomalies is calculated based on the abnormal monitoring factors and their corresponding monitoring parameters. The starting point is the time when the monitoring parameter first deviates from the standard parameter range, and the ending point is the time when the monitoring parameter returns to the normal range or monitoring ceases. The duration of anomalies is obtained by calculating the time difference between these two points. Duration of anomalies = End of monitoring time - First time of anomaly. For example, if the first time of anomaly in a drainage fluid turbidity factor is 0:00 on day 1, and the end of monitoring is 12:00 on day 1, the duration of anomalies = 12 - 0 = 12 hours. If the first time of anomaly is 0:00 on day 1, and the condition has not recovered by the end of monitoring, then the duration of anomalies = Total monitoring time - 0. Assuming the total monitoring time is 72 hours, the duration of anomalies is 72 hours.

[0039] Transient anomaly factors and persistent anomaly factors are distinguished based on the duration of the anomaly and the changing trend of the corresponding monitoring parameters. Transient anomaly factors are determined by the following criteria: the monitoring parameters deviate from the standard parameter range and then recover on their own; the duration of the anomaly is within a preset short time range; and the changing trend of the monitoring parameters shows the characteristics of initial deviation followed by a rapid return to normal, without a long-term deviation trend.

[0040] The criteria for determining a persistent abnormal factor are: the monitored parameter deviates from the standard parameter range without any recovery trend, the duration of the abnormality exceeds the preset short-term interval, and the change trend of the monitored parameter shows continuous deviation, large fluctuations, or gradually moving away from the normal range. For example, the standard parameter range for a certain drainage volume factor is 100 ml to 300 ml per day. Monitoring data shows that the drainage volume was 350 ml per day on day 1, the first abnormality occurred, and on day 2 the drainage volume recovered to 250 ml per day, returning to the standard parameter range. The duration of the abnormality is 2-1=1 day, and the parameter change trend is a brief exceedance followed by a return to the normal range. This drainage volume factor is determined to be a transient abnormal factor. Another drainage volume factor has a drainage volume of 350 ml per day on day 1, rising to 400 ml per day on day 2, and reaching 450 ml per day on day 3. The duration of the abnormality is 3-1=2 days, the parameter continues to deviate and the deviation amplitude keeps increasing, with no recovery trend. This factor is determined to be a persistent abnormal factor.

[0041] The instantaneous anomaly characteristics are obtained by integrating the peak deviation and duration of the monitoring parameters corresponding to the instantaneous anomaly factors. The peak deviation refers to the maximum deviation of the monitoring parameter from the standard parameter range. Peak deviation = maximum value of the monitoring parameter - upper limit of the standard parameter range, or peak deviation = lower limit of the standard parameter range - minimum value of the monitoring parameter. Taking the drainage volume factor of instantaneous anomaly as an example, the upper limit of the standard parameter range is 300 ml per day, the maximum value of the monitoring parameter is 350 ml per day, the peak deviation = 350 - 300 = 50 ml per day. Combined with the anomaly duration of 1 day, the integrated characteristics of this instantaneous anomaly factor are a peak deviation of 50 ml per day and a duration of 1 day, reflecting that the anomaly is a short-term, small-amplitude, and self-recoverable fluctuating anomaly.

[0042] The fluctuation patterns of monitoring parameters corresponding to persistently abnormal factors are determined, and the persistent abnormal characteristics of the abnormal monitoring factors are obtained based on these fluctuation patterns. The fluctuation patterns are determined by calculating indicators such as the fluctuation amplitude, rate of change, and deviation stability of the monitoring parameters. Fluctuation amplitude = maximum value of monitoring parameter - minimum value of monitoring parameter; rate of change = (latest value of monitoring parameter - initial value of monitoring parameter) / duration of abnormality. For example, for a persistently abnormal drainage fluid protein content factor, the standard parameter range is 15 g / L to 30 g / L, the initial monitoring value is 35 g / L, the maximum value is 38 g / L, the minimum value is 33 g / L, and the duration of abnormality is 3 days. The fluctuation amplitude is 38 - 33 = 5 g / L, and the rate of change is (33 - 35) / 3 ≈ -0.67 g / L per day. Considering the characteristics of persistent deviation and no recovery trend, its persistent abnormal characteristics are determined to be a long-term deviation from the normal range, with small fluctuation amplitude but deep deviation, and a slowly decreasing rate of change, reflecting chronic and persistent pathological abnormalities.

[0043] The patient's drainage assessment status characteristics are obtained by correlating and integrating transient and persistent abnormal features. The integration process summarizes information such as the peak deviation and duration of all transient abnormal factors, as well as the fluctuation patterns and degree of deviation of all persistent abnormal factors. These are combined with the type, quantity, and degree of influence of different abnormal factors to construct the drainage assessment status characteristics. For example, a patient may have one transient abnormal factor, characterized by a transient drainage volume exceeding the limit by 50 ml per day for one day, and two persistent abnormal factors, characterized by a persistently high and slowly fluctuating protein content in the drainage fluid. The resulting drainage assessment status characteristics would be: short-term abnormal fluctuations in drainage fluid accompanied by chronic abnormalities in drainage fluid composition.

[0044] Based on the characteristics of the drainage assessment and the pre-set abnormality handling library, the drainage treatment plan for the target patient is output.

[0045] By matching the characteristics of drainage assessment with a pre-set abnormality handling database, the system intelligently generates and outputs drainage treatment plans, providing medical staff with targeted intervention guidance for direct reference. The pre-set abnormality handling database stores standardized treatment strategies corresponding to various drainage abnormalities. Different combinations of abnormal characteristics correspond to different intervention plans, including adjustments to drainage tube care, optimization of drainage volume monitoring frequency, anti-infection interventions, and nutritional support recommendations. All plans have been clinically validated and can adapt to different degrees and types of drainage abnormalities.

[0046] The drainage assessment status characteristics of the target patient are decomposed into identifiable feature tags, including the number of transient abnormal factors, their peak deviation, and duration, as well as the fluctuation pattern and degree of deviation of persistent abnormal factors. For example, a patient's drainage assessment status characteristics might include one transient abnormal factor, a peak drainage volume deviation of 50 ml per day for one day, accompanied by two persistent abnormal factors, and persistently high and slowly fluctuating protein levels in the drainage fluid. These feature tags are then compared and matched with abnormal status entries in a pre-defined abnormality treatment library to obtain the most suitable treatment strategy combination for the patient's status characteristics.

[0047] For example, when the drainage assessment shows a transient abnormality of a small, short-term exceedance of drainage volume, the corresponding treatment plan in the pre-set abnormality treatment library is to increase the frequency of drainage fluid monitoring from once every 24 hours to once every 12 hours, while strengthening the patency check of the drainage tube and observing the trend of drainage volume changes, without the need for additional drug intervention. When the drainage assessment shows a persistent abnormality of high protein content in the drainage fluid, the corresponding treatment plan in the pre-set abnormality treatment library is to increase the patient's protein nutritional support, adjust the drainage fluid testing items, increase the daily monitoring of drainage fluid protein content, assess wound healing, investigate whether there is persistent leakage or infection risk, and adjust the anti-infection treatment plan if necessary.

[0048] The pre-set abnormality treatment library can quickly screen corresponding standardized treatment plans based on the patient's drainage assessment status characteristics, eliminating the need for medical staff to develop plans from scratch. At the same time, the plans are adapted and adjusted according to the patient's abnormal characteristics to ensure that the treatment measures not only comply with clinical norms but also fit the patient's individual drainage status. Finally, a complete drainage treatment plan is output to assist medical staff in quickly carrying out targeted interventions and improve the efficiency and accuracy of postoperative drainage management.

[0049] A system for monitoring and managing postoperative drainage fluid from pleural and abdominal fistulas includes: Acquisition module: Acquires postoperative basic information and drainage fluid monitoring data of the target patient; Processing module: Determines the corresponding drainage assessment criteria based on postoperative baseline information; the drainage assessment criteria include multiple drainage standard factors and standard parameter ranges; Extraction module: Extracts at least one drainage monitoring factor and its corresponding monitoring parameters based on the drainage fluid monitoring data; Judgment module: After matching the traffic monitoring factors with the traffic standard factors, it determines whether the monitoring parameters exceed the corresponding standard parameter range to obtain the judgment result; Determination Module: Based on the judgment results, the corresponding traffic monitoring factors are determined as abnormal monitoring factors; Generation module: Generates the drainage assessment status characteristics of the target patient based on abnormal monitoring factors and corresponding monitoring parameters; Output module: Outputs the drainage treatment plan for the target patient based on the drainage assessment status characteristics and the preset abnormality handling library.

[0050] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0051] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery, characterized in that, Includes the following steps: Obtain postoperative basic information and drainage fluid monitoring data of the target patients; The corresponding drainage assessment criteria are determined based on postoperative baseline information; wherein, the drainage assessment criteria include multiple drainage standard factors and standard parameter ranges; At least one drainage monitoring factor and its corresponding monitoring parameters were extracted from the drainage fluid monitoring data. After matching the traffic monitoring factors with the traffic standard factors, the judgment result is obtained by determining whether the monitoring parameters exceed the corresponding standard parameter range. Based on the judgment results, the corresponding drainage monitoring factors are identified as abnormal monitoring factors; Generate the drainage assessment status characteristics of the target patient based on abnormal monitoring factors and corresponding monitoring parameters; Based on the characteristics of the drainage assessment and the pre-set abnormality handling library, the drainage treatment plan for the target patient is output.

2. The method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 1, characterized in that, Determine the corresponding drainage assessment criteria based on postoperative baseline information, specifically including the following steps: Attribute information is obtained by classifying attributes from multiple dimensions based on postoperative baseline information; Based on the physiological tolerance characteristics and attribute information of drainage, suitable drainage standard factors were selected. The standard parameter range is obtained by matching the differential parameter range corresponding to the standard drainage factor based on the degree of wound leakage. The standard factors and standard parameter ranges for attracting traffic constitute the criteria for evaluating traffic.

3. The method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 2, characterized in that, At least one drainage monitoring factor and its corresponding monitoring parameters are extracted from the drainage fluid monitoring data, specifically including the following steps: The drainage fluid monitoring data were stratified and analyzed to obtain dynamic change data and static characteristic data; Based on physiological correlation characteristics, dynamic change data and static feature data are decomposed in a targeted manner to obtain data representation dimensions, and the extraction direction of drainage monitoring factors is determined according to the data representation dimensions. Based on the extraction direction, dynamic change data and static feature data are extracted to obtain the flow monitoring factor; The monitoring parameters are obtained by collecting data characterization information corresponding to the drainage monitoring factors.

4. The method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 3, characterized in that, Based on the extraction direction, dynamic change data and static feature data are extracted to obtain the traffic monitoring factors, specifically including the following steps: Based on the extraction direction, the first correlation factor reflecting the real-time fluctuation of the drainage fluid is extracted from the dynamically changing data. Based on the extraction direction, a second relevant factor reflecting the inherent properties of the drainage fluid is extracted from static feature data; The first and second relevant factors are integrated to form the drainage monitoring factor.

5. The method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 1, characterized in that, After matching the traffic diversion monitoring factors with the traffic diversion standard factors, the judgment result is obtained by determining whether the monitoring parameters exceed the corresponding standard parameter range. The specific steps include: Identify the correlation between traffic acquisition monitoring factors, and obtain factor groups by matching traffic acquisition standard factors based on the correlation; Extract the standard parameter range corresponding to the factor group; The judgment result is obtained by determining whether the monitoring parameters corresponding to the drainage monitoring factors exceed the corresponding standard parameter range.

6. A method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 5, characterized in that, Based on the judgment results, the corresponding drainage monitoring factors are identified as abnormal monitoring factors, specifically including the following steps: If the monitoring parameter corresponding to the drainage monitoring factor exceeds the standard parameter range and the first comparison result is obtained, the corresponding drainage monitoring factor will be marked as an abnormal correlation factor. If the monitoring parameters corresponding to the drainage monitoring factors do not exceed the standard parameter range and a second comparison result is obtained, then the correlation and coordination between the monitoring parameters are judged. If the correlation and coordination between the monitoring parameters shows an abnormal tendency and a third comparison result is obtained, the corresponding diversion monitoring factor will be marked as an abnormal correlation factor. The first comparison result, the second comparison result, and the third comparison result are combined to form the judgment result.

7. A method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 6, characterized in that, The drainage assessment status characteristics of the target patient are generated based on abnormal monitoring factors and corresponding monitoring parameters, specifically including the following steps: The duration of anomalies of the anomaly monitoring factors is obtained based on the anomaly monitoring factors and their corresponding monitoring parameters; The instantaneous anomaly factor and the continuous anomaly factor are obtained based on the duration of the anomaly and the changing trend of the corresponding monitoring parameters. Integrating the peak deviation and duration of the monitoring parameters corresponding to the transient anomaly factors yields the transient anomaly characteristics; Determine the fluctuation pattern of the monitoring parameters corresponding to the persistent abnormal factors, and obtain the persistent abnormal characteristics of the abnormal monitoring factors based on the fluctuation pattern; By associating and integrating transient abnormal features with persistent abnormal features, the drainage assessment status characteristics of the target patient are obtained.

8. A method for monitoring and managing postoperative drainage fluid after pleural or abdominal fistula surgery according to claim 7, characterized in that, The transient anomaly factor is a factor that recovers on its own after the monitored parameter deviates from the standard parameter range; The persistent abnormal factor is the factor whose monitored parameter deviates from the standard parameter range and shows no recovery trend.

9. A system for monitoring and processing drainage fluid after pleural or abdominal leakage surgery, applied to the method for monitoring and processing drainage fluid after pleural or abdominal leakage surgery as described in any one of claims 1 to 8, characterized in that, include: Acquisition module: Acquires postoperative basic information and drainage fluid monitoring data of the target patient; Processing module: Determines the corresponding drainage assessment criteria based on postoperative baseline information; wherein, the drainage assessment criteria include multiple drainage standard factors and standard parameter ranges; Extraction module: Extracts at least one drainage monitoring factor and its corresponding monitoring parameters based on the drainage fluid monitoring data; Judgment module: After matching the traffic monitoring factors with the traffic standard factors, it determines whether the monitoring parameters exceed the corresponding standard parameter range to obtain the judgment result; Determination Module: Based on the judgment results, the corresponding traffic monitoring factors are determined as abnormal monitoring factors; Generation module: Generates the drainage assessment status characteristics of the target patient based on abnormal monitoring factors and corresponding monitoring parameters; Output module: Outputs the drainage treatment plan for the target patient based on the drainage assessment status characteristics and the preset abnormality handling library.

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