A medical resource allocation system for combat casualty rescue

Abstract

The present invention relates to the technical field of medical resource allocation, and specifically to a medical resource allocation system for combat casualty care, comprising: obtaining monitoring curve segments corresponding to each dimensional physiological indicator of all target patients during combat casualty care at different time periods; analyzing the degree of data abnormality in each time period to screen out each abnormal monitoring curve segment corresponding to each dimensional physiological indicator of each target patient; determining the degree of abnormal change in each abnormal monitoring curve segment corresponding to each dimensional physiological indicator, and then determining the renal injury risk index of each target patient at each monitoring time, thereby determining the fluid repletion effectiveness index of each target patient at the current monitoring time; combining the fluid repletion effectiveness index and renal injury risk index of each target patient to determine the priority index for medical resource allocation for each target patient at the current monitoring time. The present invention can accurately obtain the medical resource allocation priority of different target patients during combat casualty care.

Description

Technical Field

[0001] The present invention relates to the technical field of medical resource allocation, and in particular to a medical resource allocation system for combat casualty rescue. Background Art

[0002] During wartime, the distribution of wounded is sudden and concentrated in time, and medical resources are relatively limited. Therefore, in order to effectively allocate medical resources, it is necessary to accurately analyze the condition of the wounded and determine the treatment methods for different patients based on the severity of the condition, so as to maximize the value of medical resources for wartime treatment.

[0003] Current treatment for wartime heat injuries typically uses conventional non-invasive monitoring methods to collect real-time physiological indicator data to provide feedback on the patient's vital signs. Common physiological indicator data may include heart rate, respiration, body temperature, posture, etc. However, due to the inflammatory response and tissue damage caused by heat injury, patients are at risk of acute kidney injury. Moreover, due to the influence of the complex wartime environment, the patient's condition may progress faster. At this time, the existing non-invasive monitoring methods alone cannot accurately obtain the medical resource allocation priorities for different patients. Summary of the Invention

[0004] In order to solve the technical problem that the above-mentioned existing vital sign monitoring methods cannot accurately obtain the medical resource allocation priorities of different patients, the purpose of the present invention is to provide a medical resource allocation system for combat casualty rescue. The technical solutions adopted are as follows:

[0005] One embodiment of the present invention provides a medical resource allocation system for combat casualty rescue. The allocation system includes a memory and a processor. The processor executes a computer program stored in the memory to implement the following steps:

[0006] Obtaining vital sign monitoring curves of several dimensional physiological indicators of all target patients during combat casualty rescue, and then segmenting the vital sign monitoring curves to obtain monitoring curve segments corresponding to different time periods for each dimensional physiological indicator;

[0007] According to the monitoring curve segments of different time periods corresponding to each dimensional physiological indicator of each target patient, the abnormality degree of the data in each time period is analyzed to screen out the abnormal monitoring curve segments corresponding to each dimensional physiological indicator of each target patient;

[0008] Determining the degree of abnormal change of each abnormal monitoring curve segment corresponding to each dimensional physiological indicator; determining the renal injury risk index of each target patient at each monitoring time based on the degree of abnormal change and each dimensional physiological indicator of each target patient at each monitoring time;

[0009] Obtain the corresponding renal injury risk index curve for each target patient, analyze the recovery trend of the target patient after fluid rehydration based on the segmented renal injury risk index curve, and determine the fluid rehydration effectiveness index of each target patient at the current monitoring time based on the renal injury risk index of each target patient at each monitoring time;

[0010] Combined with the fluid replacement effectiveness index and renal injury risk index of each target patient during the current monitoring, the priority index of each target patient in allocating medical resources during the current monitoring is determined.

[0011] Furthermore, the acquisition of vital sign monitoring curves of several dimensional physiological indicators of all target patients during combat casualty rescue includes:

[0012] Obtaining multiple dimensional physiological indicators of all target patients during multiple monitoring sessions during combat casualty rescue. The target patients are patients equipped with Picco monitoring equipment. The dimensional physiological indicators are mean arterial pressure, central venous pressure, or central venous oxygen saturation.

[0013] performing negative correlation processing on the mean arterial pressure of all target patients during each monitoring to obtain a negative correlation value of the mean arterial pressure, and fitting the negative correlation value of the mean arterial pressure of the same target patient during each monitoring in a time series order to obtain a time series curve of the mean arterial pressure;

[0014] The central venous pressure of the same target patient during each monitoring is fitted according to the time series order to obtain a central venous pressure time series curve; the central venous oxygen saturation of the same target patient during each monitoring is fitted according to the time series order to obtain a central venous oxygen saturation time series curve;

[0015] The vital sign monitoring curve is a mean arterial pressure time series curve, a central venous pressure time series curve or a central venous oxygen saturation time series curve.

[0016] Furthermore, the method of analyzing the abnormality of the data in each time period according to the monitoring curve segments of each target patient's physiological indicator in each dimension at different time periods to screen out the abnormal monitoring curve segments corresponding to each target patient's physiological indicator in each dimension includes:

[0017] For any time period of any dimensional physiological indicator of any target patient, determine the curve value of the starting point, the curve value of the ending point and the curve mean of the monitoring curve segment corresponding to the dimensional physiological indicator of the target patient in the time period, which are the first curve value, the second curve value and the third curve value;

[0018] Calculate the average of the curve means of the monitoring curve segments of target patients other than the target patient in the corresponding time period of the time period as the fourth curve value; wherein the corresponding time period is the time period corresponding to other target patients with the most overlapping moments with the time period;

[0019] Combine the first curve value, the second curve value, the third curve value, and the fourth curve value to analyze the growth rate of the physiological indicator of this dimension and the difference in the physiological indicator of this dimension between different target patients, and determine the degree of data abnormality in this period;

[0020] The data abnormality degree of each time period of each dimension physiological indicator of each target patient is obtained, a data abnormality threshold is set, and the monitoring curve segment of the time period with a data abnormality degree greater than the data abnormality threshold is used as an abnormal monitoring curve segment.

[0021] Furthermore, the combining of the first curve value, the second curve value, the third curve value, and the fourth curve value to analyze the growth rate of the physiological indicator of the dimension and the difference of the physiological indicator of the dimension between different target patients to determine the degree of abnormality of the data in the period includes:

[0022] Obtain the duration of the time period corresponding to the physiological indicator of the dimension of the target patient;

[0023] Calculating the difference between the second curve value and the first curve value, and taking the ratio of the difference to the duration as the first data anomaly factor for the period;

[0024] The ratio of the third curve value to the fourth curve value is used as the second data abnormality factor of the period;

[0025] Using a fusion value obtained based on the first data anomaly factor and the second data anomaly factor as the data anomaly degree of the period;

[0026] The first data anomaly factor and the second data anomaly factor are both positively correlated with the degree of data anomaly.

[0027] Furthermore, determining the abnormal change degree of each abnormal monitoring curve segment corresponding to each dimensional physiological indicator includes:

[0028] For any abnormal monitoring curve segment, obtain any abnormal monitoring curve segment adjacent to it as a comparison curve segment;

[0029] Calculate the absolute value of the difference between the data abnormality degree of the abnormal monitoring curve segment and the data abnormality degree of the comparison curve segment;

[0030] The ratio of the absolute value of the difference to the degree of data abnormality of the abnormal monitoring curve segment is used as the degree of abnormal change of the abnormal monitoring curve segment.

[0031] Furthermore, determining the renal injury risk index of each target patient at each monitoring session based on the abnormal change degree and each dimension of the physiological indicator of each target patient at each monitoring session includes:

[0032] Determine the correlation index of the physiological indicator of the target patient in the dimension according to the difference in the degree of abnormal change of the abnormal monitoring curve segment corresponding to the physiological indicator of the target patient in the dimension and that of other target patients;

[0033] Obtain the correlation index of each dimensional physiological indicator of each target patient, and use the correlation index to perform weighted summation processing on the corresponding dimensional physiological indicators of the same target patient during the same monitoring to obtain the renal injury risk index of each target patient during each monitoring.

[0034] Furthermore, analyzing the recovery trend of the target patient after fluid rehydration based on the segmented renal injury risk index curve, and determining the fluid rehydration effectiveness index of each target patient at the current monitoring time in combination with the renal injury risk index of each target patient at each monitoring time, includes:

[0035] determining extreme points of a renal injury risk index curve, segmenting the renal injury risk index curve using the extreme points, and recording a renal injury risk index curve segment containing each target patient during the current monitoring as a target curve segment;

[0036] Determining the difference between the renal injury risk index at the start time and the renal injury risk index at the end time of the target curve segment as the first recovery trend index of the corresponding target patient at the current monitoring time;

[0037] Determine the renal injury risk index of each target patient at the first monitoring as a first index, the renal injury risk index at the current monitoring as a second index, and use the ratio of the first index to the second index as a second recovery trend index;

[0038] The first recovery trend index and the second recovery trend index are combined to determine the fluid replacement effectiveness index corresponding to the target patient during the current monitoring.

[0039] Furthermore, the combining of the first recovery trend index and the second recovery trend index to determine the fluid rehydration effectiveness index corresponding to the target patient during the current monitoring includes:

[0040] For any target patient, the product of the first recovery trend index and the second recovery trend index of the target patient at the current monitoring is calculated, the product is normalized to obtain the normalized value of the product, and the normalized value of the product is used as the fluid replacement effectiveness index of the target patient at the current monitoring.

[0041] Furthermore, the step of combining the fluid replacement effectiveness index and the renal injury risk index of each target patient during the current monitoring to determine the priority index for each target patient in allocating medical resources during the current monitoring includes:

[0042] Calculate the average value of the fluid replacement effectiveness index of all target patients at the time of current monitoring, and determine the maximum value of the renal injury risk index of all target patients at the time of current monitoring;

[0043] For any target patient, the ratio of the average value to the target patient's fluid replacement effectiveness index at the time of the current monitoring is used as the first priority factor for allocating medical resources to the target patient at the time of the current monitoring;

[0044] Calculating a difference between the maximum value and the renal injury risk index of the target patient during the current monitoring, performing negative correlation processing on the difference, and using the obtained negative correlation value as the second priority factor for medical resource allocation for the target patient during the current monitoring;

[0045] The product of the first priority factor and the second priority factor is calculated, and the product of the two priority factors is normalized to obtain a priority index of the target patient when allocating medical resources during the current monitoring.

[0046] Furthermore, after obtaining the priority index of each target patient for medical resource allocation during the current monitoring, the method further includes:

[0047] The priority index of each target patient in the allocation of medical resources during the current monitoring is arranged in descending order to obtain a reference sequence for medical staff to adjust the current medical resources.

[0048] The present invention has the following beneficial effects:

[0049] The present invention provides a medical resource allocation system for combat casualty rescue. The system first obtains vital sign monitoring curves of several dimensional physiological indicators of all target patients in the combat casualty rescue process, segments the vital sign monitoring curves, and analyzes the physiological indicators of different dimensions in different time periods to screen out abnormal monitoring curve segments, so that the abnormal monitoring curve segments can be used as the main analysis objects in the subsequent analysis. This can effectively improve the efficiency of subsequent data analysis, and thus improve the calculation efficiency of priority indexes when allocating medical resources; and then determine the effective rehydration index and renal injury risk index of each target patient in the current monitoring. This helps to more accurately determine the priority index of each target patient when allocating medical resources in the current monitoring, so as to provide a reference for medical staff to allocate wartime medical resources and maximize the value of medical resources for combat casualty treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0051] Figure 1 This is a flowchart of an execution of a medical resource allocation system for combat casualty rescue according to the present invention;

[0052] Figure 2 Flowchart for implementing step S2 in an embodiment of the present invention;

[0053] Figure 3 Flowchart for implementing step S32 in an embodiment of the present invention;

[0054] Figure 4 This is a flowchart for implementing step S4 in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] To further illustrate the technical means and effects employed by the present invention to achieve its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementations, structures, features, and effects of the technical solutions proposed by the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0056] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0057] Application scenarios targeted by this invention:

[0058] To analyze the progression of different patients' conditions during combat rescue and their likelihood of developing acute kidney injury, and to more accurately prioritize medical resource allocation, this invention monitors pulse contour cardiac output (Picco) in patients with thermal injuries. Based on the acquired data and correlations between various indicators, the effectiveness of post-burn fluid rehydration in different patients is analyzed. This effectiveness is then used to analyze the progression of each patient's condition and determine the severity of each patient's condition, providing a reference for medical staff to allocate wartime medical resources. Pulse contour cardiac output is the collective term for all dimensional physiological indicators detected by Picco equipment.

[0059] This embodiment provides a medical resource allocation system for combat casualty rescue, including a memory and a processor, wherein the processor executes a computer program stored in the memory to implement the following steps:

[0060] Obtaining vital sign monitoring curves of several dimensional physiological indicators of all target patients during combat casualty rescue, and then segmenting the vital sign monitoring curves to obtain monitoring curve segments corresponding to different time periods for each dimensional physiological indicator;

[0061] According to the monitoring curve segments of different time periods corresponding to each dimensional physiological indicator of each target patient, the abnormality degree of the data in each time period is analyzed to screen out the abnormal monitoring curve segments corresponding to each dimensional physiological indicator of each target patient;

[0062] Determining the degree of abnormal change of each abnormal monitoring curve segment corresponding to each dimensional physiological indicator; determining the renal injury risk index of each target patient at each monitoring time based on the degree of abnormal change and each dimensional physiological indicator of each target patient at each monitoring time;

[0063] Obtain the corresponding renal injury risk index curve for each target patient, analyze the recovery trend of the target patient after fluid rehydration based on the segmented renal injury risk index curve, and determine the fluid rehydration effectiveness index of each target patient at the current monitoring time based on the renal injury risk index of each target patient at each monitoring time;

[0064] Combined with the fluid replacement effectiveness index and renal injury risk index of each target patient during the current monitoring, the priority index of each target patient in the allocation of medical resources during the current monitoring is determined.

[0065] The following is a detailed explanation of each of the above steps:

[0066] refer to Figure 1 , shows an execution flow chart of a medical resource allocation system for combat casualty rescue according to the present invention, including:

[0067] S1, obtain the vital sign monitoring curves of several dimensional physiological indicators of all target patients in the combat casualty rescue process, and then segment the vital sign monitoring curves to obtain monitoring curve segments corresponding to different time periods for each dimensional physiological indicator.

[0068] The above step S1 can be implemented through steps S11 to S12 (not shown):

[0069] S11, obtain vital sign monitoring curves of several dimensional physiological indicators of all target patients during combat casualty rescue.

[0070] The above step S11 can be implemented through steps S111 to S113 (not shown):

[0071] S111, obtain several dimensional physiological indicators of all target patients during several monitoring sessions during combat casualty rescue.

[0072] Here, the target patients are those who have Picco monitoring devices installed, that is, patients who are diagnosed by doctors as needing to be monitored by Picco monitoring devices, that is, patients with thermal damage caused by wartime burns combined with early acute kidney injury. The dimensional physiological indicators are mean arterial pressure, central venous pressure or central venous oxygen saturation.

[0073] In this embodiment, the mean arterial pressure, central venous pressure, or central venous oxygen saturation of all target patients is collected at each monitoring session during combat casualty care, starting from the time the patient is diagnosed as requiring Picco monitoring by a physician until the physician determines that monitoring is no longer necessary. The interval between two consecutive monitoring sessions can be four hours, and the implementer can adjust the monitoring interval based on specific circumstances.

[0074] Patients who require Picco monitoring are generally burn patients. For patients with thermal damage caused by wartime burns and early acute kidney injury, it is necessary to establish an intravenous channel for rapid fluid infusion and fluid resuscitation. The reason is that the possibility of burns in wartime is greater than the possibility of daily burns. After a burn, the heat will damage the skin tissue, causing a large amount of fluid in the blood vessels to extravasate, reducing the effective circulating blood volume, resulting in insufficient perfusion of the renal tissue, thereby reducing renal function and even causing renal damage. Therefore, patients with more severe burns need to undergo fluid replenishment and recovery under Picco monitoring to prevent and alleviate the occurrence of acute kidney injury in patients.

[0075] Specifically, the patient is placed in a supine position, and a triple-lumen central venous catheter is inserted into the subclavian vein at a depth of approximately 14 cm. A Picco arterial temperature and pressure catheter is then inserted into the femoral artery. Both the Picco arterial temperature and pressure catheter and the triple-lumen central venous catheter are connected to a monitor. A single patient's Picco monitoring device is a monitoring terminal. In the multi-dimensional intelligent vital signs monitoring system for wartime burn rescue, a monitoring group consists of multiple portable monitoring terminals and a central monitoring terminal. Physiological data is wirelessly transmitted to the central monitoring terminal for display, analysis, diagnosis, and storage. Multiple portable monitoring terminals and the central monitoring terminal can form a regional wireless network.

[0076] S112, performing negative correlation processing on the mean arterial pressure of all target patients during each monitoring to obtain negative correlation values ​​of the mean arterial pressure, and fitting the negative correlation values ​​of the mean arterial pressure of the same target patient during each monitoring in a time series order to obtain a time series curve of the mean arterial pressure.

[0077] Because a decrease in mean arterial pressure may worsen a patient's renal function, mean arterial pressure is negatively correlated with the renal injury risk index subsequently analyzed. To facilitate data analysis, this embodiment performs negative correlation processing on the collected mean arterial pressure, such as taking the inverse of the mean arterial pressure as the negative correlation value of the mean arterial pressure. To analyze the overall growth of mean arterial pressure, a curve is fitted to the negative correlation values ​​of the mean arterial pressure of the same target patient at each monitoring session, using the least squares method in a time series order. The resulting curve is used as the mean arterial pressure time series curve. The implementation of the negative correlation processing and least squares method for the data are both prior art and are outside the scope of protection of the present invention, and will not be elaborated on in detail here.

[0078] S113, fitting the central venous pressure of the same target patient during each monitoring according to the time sequence to obtain a central venous pressure time series curve; fitting the central venous oxygen saturation of the same target patient during each monitoring according to the time sequence to obtain a central venous oxygen saturation time series curve.

[0079] For central venous pressure and central venous oxygen saturation, increases in central venous pressure and oxygen saturation may worsen the patient's renal function. Therefore, in order to facilitate the analysis of the growth trend of the monitoring data, the least squares method can be used to fit the central venous pressure and central venous oxygen saturation of the same target patient at all monitoring times in a chronological order to obtain two fitting curves, namely the central venous pressure time series curve and the central venous oxygen saturation time series curve.

[0080] It should be noted that, under normal circumstances, the collection and termination times of the target patient's different dimensional physiological indicators are the same, so the total duration corresponding to the mean arterial pressure time series curve, central venous pressure time series curve, and central venous oxygen saturation time series curve is the same, and each target patient has three corresponding different vital sign monitoring curves, which can be the mean arterial pressure time series curve, the central venous pressure time series curve, or the central venous oxygen saturation time series curve. Among them, the horizontal axis of the vital sign monitoring curve can be the monitoring time point, and the vertical axis can be the dimensional physiological indicator.

[0081] S12, segmenting the vital sign monitoring curve to obtain monitoring curve segments corresponding to different time periods of each dimensional physiological indicator.

[0082] Since the disease progression of different patients is different and the growth trends of physiological indicators in different dimensions are different, this embodiment segments the vital sign monitoring curve at each extreme point to obtain monitoring curve segments for different time periods corresponding to each dimensional physiological indicator.

[0083] So far, this embodiment has obtained the monitoring curve segments of different time periods corresponding to each dimensional physiological indicator of each target patient.

[0084] S2, according to the monitoring curve segments of different time periods corresponding to each dimensional physiological indicator of each target patient, analyze the abnormality degree of the data in each time period to screen out the abnormal monitoring curve segments corresponding to each dimensional physiological indicator of each target patient.

[0085] Here, the abnormal monitoring curve segment refers to the abnormal situation of the dimensional physiological indicator data of a patient in a certain period of time. The more abnormal the dimensional physiological indicator data is, the more likely the patient's condition is to be more serious. By screening out the abnormal monitoring curve segments, the computational complexity of subsequent data analysis can be reduced to a certain extent, which helps to improve the efficiency of patient vital signs analysis.

[0086] Taking the first dimension physiological index of the i-th target patient as an example, the abnormal monitoring curve segments corresponding to the first dimension physiological index of the i-th target patient are determined. The above step S2 can be performed by Figure 2 The steps S21 to S24 shown implement:

[0087] S21, for the j-th time period of the first-dimensional physiological indicator of the i-th target patient, determine the curve value of the starting point, the curve value of the ending point and the curve mean in the monitoring curve segment of the j-th time period corresponding to the first-dimensional physiological indicator of the i-th target patient, which are the first curve value, the second curve value and the third curve value.

[0088] In this embodiment, the first dimensional physiological indicator can be mean arterial pressure, central venous pressure, or central venous oxygen saturation. The curve value at the starting point refers to the dimensional physiological indicator of the monitoring curve segment of the jth time period at the first time point, and the end point refers to the dimensional physiological indicator at the last time point. The curve value at the starting point corresponds to the first curve value, the curve value at the end point corresponds to the second curve value, and the curve mean corresponds to the third curve value. The curve mean refers to the average value of all curve values ​​in the monitoring curve segment of the jth time period.

[0089] S22, calculating the average of the curve means of the monitoring curve segments of the target patients other than the i-th target patient in the corresponding time period of the j-th time period as the fourth curve value.

[0090] In this embodiment, the corresponding time period is the time period corresponding to other target patients with the most repeated moments with the j-th time period. For the j-th time period, each other target patient corresponds to a corresponding time period. When calculating the four curve values, the average value of all curve means is calculated again on the premise of calculating the curve mean of the monitoring curve segments of the corresponding time periods of all target patients except the i-th target patient.

[0091] S23, combining the first curve value, the second curve value, the third curve value and the fourth curve value to analyze the growth rate of the first dimension physiological indicator and the difference in the first dimension physiological indicator between different target patients, and determine the degree of data abnormality in the jth time period.

[0092] In this embodiment, if the growth rate of the dimensional physiological indicators of a target patient in a certain period is large, and the dimensional physiological indicator values ​​are larger than those of all other target patients in the corresponding period, it means that the data abnormality of the dimensional physiological indicators of the target patient in this period is large.

[0093] The above step S23 can be implemented by the following steps:

[0094] Obtain the duration of the jth period of the first dimension physiological indicator for the i-th target patient; calculate the difference between the second curve value and the first curve value, and use the ratio of the difference to the duration as the first data anomaly factor for the j-th period; use the ratio of the third curve value to the fourth curve value as the second data anomaly factor for the j-th period; and use the fusion value obtained based on the first and second data anomaly factors as the degree of data anomaly for the j-th period. The first and second data anomaly factors are both positively correlated with the degree of data anomaly, and the fusion value can be the product of the two data anomaly factors.

[0095] As an example, the calculation process of the data abnormality degree of the first dimension physiological indicator of the i-th target patient in the j-th period includes:

[0096] Where, represents the fusion value of the first dimension physiological indicator of the i-th target patient in the j-th period, i represents the i-th target patient, j represents the j-th period, and r represents the end point. l Indicates the starting point, represents the second curve value of the first dimension physiological indicator of the i-th target patient in the j-th period, represents the first curve value of the first dimension physiological indicator of the i-th target patient in the j-th period, represents the duration of the jth period of the first dimension physiological indicator of the i-th target patient, Represents the first data abnormality factor of the first dimension physiological indicator of the i-th target patient in the j-th period, represents the third curve value of the first dimension physiological indicator of the i-th target patient in the j-th period, represents the fourth curve value, Represents the second data abnormality factor of the j-th period of the first dimension physiological indicator of the i-th target patient.

[0097] In the calculation formula for the fusion value, a larger first data anomaly factor indicates a greater increase in the first dimension physiological indicator of the i-th target patient during the j-th period. A larger second data anomaly factor indicates that, in the corresponding period of the j-th period, the first dimension physiological indicator of the i-th target patient is larger than that of the other target patients, and the greater the degree of data anomaly of the first dimension physiological indicator of the i-th target patient during the j-th period. It is worth noting that under normal circumstances, the fourth curve value has no possibility of being zero. In extreme cases, a non-zero constant, such as 0.01, is added to the denominator of the second data anomaly factor to avoid the possibility of the denominator of the fraction being zero.

[0098] The fused value of the first dimension physiological indicator of the i-th target patient at the j-th time period is normalized, and the normalized fused value is used as the data abnormality level, and the value range of the data abnormality level is between 0 and 1. The normalization method can be a linear function or a maximum and minimum value method. The implementation process of the normalization process is prior art and is not within the scope of protection of the present invention, and will not be elaborated here.

[0099] S24, obtaining the data abnormality degree of each time period of the first dimension physiological indicator of the i-th target patient, setting a data abnormality threshold, and taking the monitoring curve segment of the time period where the data abnormality degree is greater than the data abnormality threshold as the abnormal monitoring curve segment.

[0100] In this embodiment, referring to the calculation process of the data abnormality degree of the jth time period of the first dimension physiological indicator of the i-th target patient, the data abnormality degree of each time period of the first dimension physiological indicator of the i-th target patient can be obtained. The data abnormality threshold can be set to 0.7, and the monitoring curve segments of the time period with a data abnormality degree greater than 0.7 are used as abnormal monitoring curve segments, thereby obtaining each abnormal monitoring curve segment corresponding to the first dimension physiological indicator of the i-th target patient. Among them, the data abnormality threshold can be set by the implementer according to the specific actual situation and is not specifically limited here.

[0101] At this point, through the above steps S21 to S24, each abnormal monitoring curve segment corresponding to each dimensional physiological indicator of each target patient can be obtained.

[0102] S3, determining the degree of abnormal change of each abnormal monitoring curve segment corresponding to each dimensional physiological indicator; determining the renal injury risk index of each target patient at each monitoring time based on the degree of abnormal change and each dimensional physiological indicator of each target patient at each monitoring time.

[0103] Here, the renal injury risk index refers to the possibility of the target patient suffering from renal injury at each monitoring. The larger the renal injury risk index is, the more urgent the treatment stage is, and the higher the probability of prioritizing the allocation of medical resources to the target patient is.

[0104] Patients with more severe burns need to maintain their circulating blood volume and renal perfusion pressure through fluid resuscitation to reduce the current risk of renal injury in patients. As fluid resuscitation progresses, the physiological indicators of various dimensions monitored by Picco also change accordingly. That is, the degree of disease progression of the target patient at a certain moment is reflected by the changes in the physiological indicators of various dimensions monitored by Picco, and there is a certain correlation between the changing trends of the physiological indicators of various dimensions. Therefore, in order to obtain the renal injury risk of the target patient at each monitoring, it is necessary to conduct data analysis based on the values ​​of the physiological indicators of specific dimensions and the correlation between the physiological indicators of various dimensions of the same target patient.

[0105] The above step S3 can be implemented through steps S31 to S32 (not shown):

[0106] S31, determining the abnormal change degree of each abnormal monitoring curve segment corresponding to each dimensional physiological indicator according to the difference between the data abnormality degrees of two adjacent abnormal monitoring curve segments.

[0107] Taking a single-dimensional physiological indicator of the target patient as an example, if the change in the abnormality of the data in the abnormal monitoring curve segment of the physiological indicator of this dimension can cause a large degree of fluctuation in the abnormalities of other pulse contour and cardiac output indicators, that is, the physiological indicator of this dimension can greatly affect the current physiological state of the target patient, then it indicates that there is a possibility of a greater risk of renal damage.

[0108] Specifically, for any abnormal monitoring curve segment, any abnormal monitoring curve segment adjacent to it is obtained as a comparison curve segment; the absolute value of the difference between the data abnormality degree of the abnormal monitoring curve segment and the data abnormality degree of the comparison curve segment is calculated; and the ratio of the absolute value of the difference to the data abnormality degree of the abnormal monitoring curve segment is used as the abnormal change degree of the abnormal monitoring curve segment.

[0109] In this embodiment, taking the kth abnormal monitoring curve segment corresponding to the first dimension physiological indicator of the i-th target patient as an example, the calculation formula for the abnormal change degree of the kth abnormal monitoring curve segment corresponding to the first dimension physiological indicator can be:

[0110] Where, Indicates the abnormal change degree of the kth abnormal monitoring curve segment corresponding to the first dimension physiological indicator of the i-th target patient, Indicates the data abnormality degree of the kth abnormal monitoring curve segment corresponding to the first dimension physiological indicator of the i-th target patient, Indicates the first dimension physiological index corresponding to the i-th target patient The degree of data abnormality of each abnormal monitoring curve segment, Represents the absolute value function.

[0111] By referring to the calculation process of the abnormal change degree of the kth abnormal monitoring curve segment corresponding to the first dimension physiological indicator of the i-th target patient, the abnormal change degree of each abnormal monitoring curve segment corresponding to each dimension physiological indicator of each target patient can be obtained.

[0112] S32, determining the renal injury risk index of each target patient at each monitoring session based on the degree of abnormal changes and each dimension of the physiological indicators of each target patient at each monitoring session.

[0113] The above step S32 can be Figure 3 Steps S321 to S322 shown implement:

[0114] S321, determining a correlation index of the target patient's physiological indicator in the dimension based on the difference in abnormal change degree between the abnormal monitoring curve segments corresponding to the physiological indicators of the target patient and other target patients in the same dimension.

[0115] In this embodiment, if the data abnormality degree changes of the target patient's physiological indicators of other dimensions other than the first dimension physiological indicator are relatively similar to those of the first dimension physiological indicator in the corresponding abnormal monitoring curve segments, that is, except for the first dimension physiological indicator, the physiological indicators of the other dimensions have the same degree of abnormality at the same time in the corresponding time period, then it means that the correlation index of the first dimension physiological indicator is larger.

[0116] As an example, the calculation formula for the correlation index of the physiological indicators of the first dimension of the i-th target patient can be:

[0117] Where, represents the correlation index of the physiological indicators of the i-th target patient in the first dimension, represents the number of abnormal monitoring curve segments corresponding to the physiological indicators of the first dimension of the i-th target patient, Indicates the physiological index of the i-th target patient in the first dimension corresponding to the The abnormal change degree of the abnormal monitoring curve segment in the corresponding period of the abnormal monitoring curve segment of the physiological indicators of other dimensions except the first dimension physiological indicators, Indicates the physiological index of the i-th target patient in the first dimension corresponding to the The abnormal change degree of each abnormal monitoring curve segment, Find the absolute value function.

[0118] In the calculation formula of the correlation index, Indicates the physiological index of the i-th target patient in the first dimension corresponding to the The difference between the abnormal change degree of an abnormal monitoring curve segment and the abnormal change degree of the corresponding period of the other dimensional physiological indicators, It represents the sum of the differences between the abnormal change degree of all abnormal monitoring curve segments corresponding to the physiological indicators of the first dimension of the i-th target patient and the abnormal change degree of the corresponding time period of the physiological indicators of the other dimensions. The larger the sum of the differences, the greater the impact of the physiological indicators of the first dimension of the i-th target patient on the risk of renal injury, that is, the greater the correlation index of the physiological indicators of the first dimension of the i-th target patient. It is worth noting that under normal circumstances, There is no possibility of the value being zero. If there is an extreme case, A non-zero constant, such as 0.01, is added to the denominator of the fraction to avoid the possibility of the denominator being zero.

[0119] S322, obtaining the correlation index of each dimensional physiological indicator of each target patient, and using the correlation index to perform weighted summation processing on the corresponding dimensional physiological indicators of the same target patient during the same monitoring, to obtain the renal injury risk index of each target patient during each monitoring.

[0120] In this embodiment, referring to the calculation process of the correlation index of the physiological indicator of the first dimension for the i-th target patient, the correlation index of each physiological indicator of each dimension for each target patient can be obtained. It is worth noting that the correlation index of the same target patient under the same physiological indicator of the dimension is the same for all monitoring times.

[0121] Based on the degree of influence of the physiological indicators of each dimension on the current renal injury risk of the i-th target patient at the m-th monitoring, that is, the correlation index of the physiological indicators of the i-th target patient in the z-th dimension, combined with the physiological indicators of the i-th target patient in the z-th dimension at the m-th monitoring, the renal injury risk index of the i-th target patient at the m-th monitoring was analyzed.

[0122] As an example, the calculation formula for the renal injury risk index of the i-th target patient at the m-th monitoring time can be:

[0123] Where, represents the renal injury risk index of the i-th target patient at the m-th monitoring time, Represents a normalization function whose value range is between 0 and 1. represents the number of dimensional physiological indicators, z represents the physiological indicator of the zth dimension, Represents the correlation index of the z-th dimension physiological index of the i-th target patient, which is equivalent to The weight of Represents the z-th dimension physiological indicator of the i-th target patient at the m-th monitoring time.

[0124] In the calculation formula of the renal injury risk index, in order to facilitate subsequent mathematical calculations, the value range of the renal injury risk index is between 0 and 1. By comprehensively analyzing the physiological indicators of different dimensions of the same target patient, the possibility of the target patient being at risk of renal injury at each monitoring can be quantified, which helps to subsequently determine the effectiveness of fluid replacement and the priority index when allocating medical resources.

[0125] At this point, by referring to the calculation process of the renal injury risk index of the i-th target patient at the m-th monitoring, the renal injury risk index of each target patient at each monitoring can be obtained.

[0126] S4, obtain the renal injury risk index curve corresponding to each target patient, analyze the recovery trend of the target patient after fluid repletion based on the segmented renal injury risk index curve, and determine the fluid repletion effectiveness index of each target patient at the time of the current monitoring based on the renal injury risk index of each target patient at each monitoring.

[0127] Here, the fluid replacement effectiveness index can represent the effectiveness of the fluid replacement process for the target patient during the combat injury rescue stage. The larger the fluid replacement effectiveness index is, the better the target patient is in the recovery stage, and the lower the priority of medical resource allocation.

[0128] Since the initial severity of burns varies among different target patients and the wartime environment is complex, the degree of impact on different burn patients varies. Specific fluid rehydration plans and individual physical conditions also vary. Fluid rehydration plans can be formulated by doctors so that the degree of change in physiological indicators of different patients as the fluid replenishment process changes. That is, the degree of fluid rehydration effectiveness of different target patients at different monitoring times is different. Therefore, by analyzing the degree of change in the target patient's renal injury risk over time, the target patient's fluid rehydration effectiveness index can be obtained.

[0129] In this embodiment, if the renal injury risk of a target patient shows a decreasing trend and is significantly lower than the renal injury risk after the initial burn, it means that the fluid rehydration effect of the target patient under the current monitoring is better and the degree of recovery is higher.

[0130] The above step S4 can be Figure 4 Steps S41 to S45 shown implement:

[0131] S41, obtaining a renal injury risk index curve corresponding to each target patient.

[0132] In this embodiment, in order to analyze the overall trend change of the renal injury risk of the same target patient, the least squares method is used to perform curve fitting on all renal injury risk indices of the same target patient, and a renal injury risk index curve corresponding to each target patient can be obtained.

[0133] S42, determining each extreme point of the renal injury risk index curve, segmenting the renal injury risk index curve using the extreme points, and recording the renal injury risk index curve segment containing each target patient during the current monitoring as the target curve segment.

[0134] In this embodiment, when allocating medical resources, the priority is mainly based on the patient's condition at the time of the most recent monitoring. Therefore, it is only necessary to obtain the target curve segment as the segmented renal injury risk index curve. The target curve segment refers to the curve segment that contains the renal injury risk index of the current monitoring. Each target patient has its corresponding target curve segment. Compared with analyzing the entire renal injury risk index curve, only analyzing the target curve segment can not only reduce the amount of data analysis, but also improve the accuracy of the subsequent determination of the effective index of fluid rehydration. Among them, the process of obtaining the extreme points in the curve is a prior art and is not within the scope of protection of the present invention. It will not be elaborated here.

[0135] S43: Determine the difference between the renal injury risk index at the start moment and the renal injury risk index at the end moment of the target curve segment as the first recovery trend index of the corresponding target patient during the current monitoring.

[0136] In this embodiment, the larger the first recovery trend index is, the more obvious the trend of decreasing risk of renal injury is, the better the fluid replacement effect of the target patient during the current monitoring is, and the higher the recovery degree of the target patient is; on the contrary, the smaller the first recovery trend index is, the less obvious the trend of decreasing risk of renal injury is, the worse the fluid replacement effect of the target patient during the current monitoring is, and the lower the recovery degree of the target patient is.

[0137] S44, determining the renal injury risk index of each target patient at the first monitoring as the first index, the renal injury risk index at the current monitoring as the second index, and taking the ratio of the first index to the second index as the second recovery trend index.

[0138] In this embodiment, the second recovery trend index is larger, indicating that the renal injury risk index at the time of the current monitoring is significantly lower than the renal injury risk after the initial burn, and the target patient has a better fluid replacement effect at the time of the current monitoring; on the contrary, the second recovery trend index is smaller, indicating that the renal injury risk index at the time of the current monitoring is less reduced than the renal injury risk after the initial burn, and the target patient has a poor fluid replacement effect at the time of the current monitoring.

[0139] S45 , combining the first recovery trend index and the second recovery trend index to determine a fluid infusion effectiveness index corresponding to the target patient during the current monitoring.

[0140] In this embodiment, the first recovery trend index, the second recovery trend index and the fluid replacement effectiveness index are all positively correlated.

[0141] As an example, the step of determining the fluid replacement effectiveness index corresponding to the target patient during the current monitoring may include:

[0142] For any target patient, the product of the first recovery trend index and the second recovery trend index of the target patient at the time of the current monitoring is calculated, the product is normalized to obtain a normalized value of the product, and the normalized value of the product is used as the fluid replacement effectiveness index of the target patient at the time of the current monitoring. The normalization process can be implemented by a linear normalization function.

[0143] So far, this embodiment has obtained the fluid replacement effectiveness index of each target patient during the current monitoring.

[0144] S5. Combine the fluid replacement effectiveness index and renal injury risk index of each target patient during the current monitoring to determine the priority index of each target patient for allocating medical resources during the current monitoring.

[0145] Here, the priority index refers to the priority of the current target patient when allocating medical resources. The larger the priority index, the earlier the target patient can be allocated medical resources for treatment.

[0146] Since wartime burns occur more frequently and medical resources are more limited, in order to rationally allocate existing resources, it is necessary to quantify the severity of the disease based on the fluid replacement effectiveness index and kidney injury risk index of all current target patients, and then determine the priority index for allocating medical resources to the current target patients.

[0147] In this embodiment, if the effectiveness of fluid rehydration for a target patient is worse during the last monitoring and the risk of renal injury is greater than that of target patients other than the target patient, it means that the condition of the target patient is more critical and the priority of allocating medical resources to the target patient is higher.

[0148] The above step S5 can be implemented through steps S51 to S54 (not shown):

[0149] S51, calculating the average value of the fluid replacement effectiveness index of all target patients during the current monitoring, and determining the maximum value of the renal injury risk index of all target patients during the current monitoring.

[0150] S52: For any target patient, the ratio of the average value to the target patient's fluid replacement effectiveness index during the current monitoring is used as the first priority factor for allocating medical resources to the target patient during the current monitoring.

[0151] S53, calculating the difference between the maximum value and the renal injury risk index of the target patient during the current monitoring, performing negative correlation processing on the difference, and using the obtained negative correlation value as the second priority factor for medical resource allocation for the target patient during the current monitoring.

[0152] S54, calculating the product of the first priority factor and the second priority factor, normalizing the product of the two priority factors, and obtaining a priority index for the target patient when allocating medical resources during the current monitoring.

[0153] As an example, the calculation formula for the priority index of the i-th target patient when allocating medical resources during the current monitoring period can be:

[0154] Where, It represents the priority index of the i-th target patient in the allocation of medical resources during the current monitoring. It represents the average value of the effective rehydration index of all target patients at the time of current monitoring. represents the effective index of fluid rehydration of the i-th target patient during the current monitoring. Indicates the maximum value of the renal injury risk index of all target patients at the time of current monitoring. represents the renal injury risk index of the i-th target patient at the time of current monitoring, It represents the first priority factor for allocating medical resources to the i-th target patient during the current monitoring. represents the second priority factor for allocating medical resources to the i-th target patient during the current monitoring, and norm represents the linear normalization function.

[0155] In the calculation formula of the priority index, Indicates the difference between the renal injury risk index of the current target patient and the maximum renal injury risk index of all patients. The smaller the value, the greater the renal injury risk of the current target patient, and the higher the priority for medical resource allocation; Indicates the difference between the effective fluid replacement index of the current target patient and the average effective fluid replacement index of all target patients. The larger it is, the worse the effectiveness of the current target patient's fluid replacement is, and the higher the priority of medical resource allocation is. It is worth noting that under normal circumstances, and There is no possibility of the value being zero. If there is an extreme case, A non-zero constant, such as 0.01, is added to the denominator of the fraction to avoid the possibility of the denominator being zero.

[0156] After obtaining the priority index of each target patient for medical resource allocation during the current monitoring, it also includes:

[0157] In this embodiment, the central monitoring terminal is used to sequentially output the priority index of each target patient when allocating medical resources during the current monitoring, that is, the priority index of each target patient when allocating medical resources during the current monitoring is output sequentially in descending order, and the sorted priority index sequence is used as a reference sequence for medical staff when adjusting the current medical resources, so as to provide a reference for medical staff to adjust medical resources.

[0158] So far, this embodiment has obtained the priority of medical resource allocation for all current target patients.

[0159] In summary, based on the characteristics of wartime burn incidents that are relatively concentrated and medical resources are limited, the present invention uses Picco equipment to monitor patients' vital signs, thereby analyzing their risk of renal injury and the effectiveness of fluid rehydration for the patients. Combined with the progression of the disease of all patients, the priority index for allocating medical resources to each patient is analyzed, thus providing a reference for medical staff to allocate current medical resources.

[0160] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A medical resource allocation system for combat casualty rescue, characterized in that: The distribution system includes a memory and a processor, wherein the processor is configured to process instructions stored in the memory to implement the following steps: Obtain vital sign monitoring curves of several dimensional physiological indicators for all target patients during combat casualty rescue, and then segment the vital sign monitoring curves to obtain monitoring curve segments corresponding to different time periods for each dimensional physiological indicator; According to the monitoring curve segments of different time periods corresponding to each dimensional physiological indicator of each target patient, the abnormality degree of the data in each time period is analyzed to screen out the abnormal monitoring curve segments corresponding to each dimensional physiological indicator of each target patient; Determine the degree of abnormal change of each abnormal monitoring curve segment corresponding to each dimension of physiological indicators; Determine the renal injury risk index of each target patient at each monitoring session based on the degree of abnormal changes and each dimension of physiological indicators of each target patient at each monitoring session; Obtain the corresponding renal injury risk index curve for each target patient, analyze the recovery trend of the target patient after fluid rehydration based on the segmented renal injury risk index curve, and determine the fluid rehydration effectiveness index of each target patient at the current monitoring time based on the renal injury risk index of each target patient at each monitoring time; Combined with the fluid replacement effectiveness index and renal injury risk index of each target patient during the current monitoring, determine the priority index of each target patient in allocating medical resources during the current monitoring; Obtaining vital sign monitoring curves of several dimensional physiological indicators of all target patients during combat casualty rescue, including: obtaining several dimensional physiological indicators of all target patients during several monitoring sessions during combat casualty rescue, where the target patients are patients equipped with Picco monitoring equipment, and the dimensional physiological indicators are mean arterial pressure, central venous pressure, or central venous oxygen saturation; performing negative correlation processing on the mean arterial pressure of all target patients during each monitoring session to obtain a negative correlation value of the mean arterial pressure, fitting the negative correlation value of the mean arterial pressure of the same target patient during each monitoring session in a time series order to obtain a mean arterial pressure time series curve; fitting the central venous pressure of the same target patient during each monitoring session in a time series order to obtain a central venous pressure time series curve; fitting the central venous oxygen saturation of the same target patient during each monitoring session in a time series order to obtain a central venous oxygen saturation time series curve; the vital sign monitoring curve is a mean arterial pressure time series curve, a central venous pressure time series curve, or a central venous oxygen saturation time series curve; Based on the degree of abnormal change and each dimensional physiological indicator of each target patient at each monitoring, the renal injury risk index of each target patient at each monitoring is determined, including: determining the correlation index of the target patient's physiological indicator in the dimension based on the difference between the degree of abnormal change of the abnormal monitoring curve segment corresponding to the physiological indicator of the same dimension of any target patient and other target patients; obtaining the correlation index of each dimensional physiological indicator of each target patient, and using the correlation index to perform weighted summation processing on the corresponding dimensional physiological indicators of the same target patient at the same monitoring, to obtain the renal injury risk index of each target patient at each monitoring.

2. A medical resource allocation system for combat casualty rescue according to claim 1, characterized in that: According to the monitoring curve segments of different time periods corresponding to each dimension of physiological indicators of each target patient, the abnormality of the data in each time period is analyzed to screen out the abnormal monitoring curve segments corresponding to each dimension of physiological indicators of each target patient, including: For any time period of any dimensional physiological indicator of any target patient, determine the curve value of the starting point, the curve value of the ending point and the curve mean of the monitoring curve segment corresponding to the dimensional physiological indicator of the target patient in the time period, which are the first curve value, the second curve value and the third curve value; Calculate the average of the curve means of the monitoring curve segments of other target patients other than the target patient in the corresponding time period of the time period as the fourth curve value; wherein the corresponding time period is the time period corresponding to other target patients with the most overlapping moments with the time period; Combine the first curve value, the second curve value, the third curve value, and the fourth curve value to analyze the growth rate of the physiological indicator of this dimension and the difference in the physiological indicator of this dimension between different target patients, and determine the degree of data abnormality in this period; Obtain the data abnormality degree of each dimension physiological indicator of each target patient in each time period, set the data abnormality threshold, and use the monitoring curve segment of the time period where the data abnormality degree is greater than the data abnormality threshold as the abnormal monitoring curve segment.

3. A medical resource allocation system for combat casualty rescue according to claim 2, characterized in that: Combine the first curve value, the second curve value, the third curve value, and the fourth curve value to analyze the growth rate of the physiological indicator of this dimension and the difference in the physiological indicator of this dimension between different target patients, and determine the degree of data abnormality in this period, including: Obtain the duration of the time period corresponding to the physiological indicator of the dimension of the target patient; Calculate the difference between the second curve value and the first curve value, and use the ratio of the difference to the duration as the first data anomaly factor for the period; The ratio of the third curve value to the fourth curve value is used as the second data abnormality factor of the period; The fusion value obtained based on the first data anomaly factor and the second data anomaly factor is used as the data anomaly degree of the period; Among them, the first data anomaly factor and the second data anomaly factor are both positively correlated with the degree of data anomaly.

4. A medical resource allocation system for combat casualty rescue according to claim 1, characterized in that: Determine the degree of abnormal change of each abnormal monitoring curve segment corresponding to each dimension of physiological indicators, including: For any abnormal monitoring curve segment, obtain any abnormal monitoring curve segment adjacent to it as a comparison curve segment; Calculate the absolute value of the difference between the data abnormality degree of the abnormal monitoring curve segment and the data abnormality degree of the comparison curve segment; The ratio of the absolute value of the difference to the degree of data abnormality of the abnormal monitoring curve segment is used as the degree of abnormal change of the abnormal monitoring curve segment.

5. The medical resource allocation system for combat casualty rescue according to claim 1, characterized in that: The recovery trend of the target patient after fluid rehydration is analyzed based on the segmented renal injury risk index curve. Combined with the renal injury risk index of each target patient at each monitoring session, the fluid rehydration effectiveness index of each target patient at the current monitoring session is determined, including: Determine each extreme point of the renal injury risk index curve, segment the renal injury risk index curve using the extreme points, and record the renal injury risk index curve segment containing each target patient during the current monitoring as the target curve segment; Determining the difference between the renal injury risk index at the start time and the renal injury risk index at the end time of the target curve segment as the first recovery trend index of the corresponding target patient at the current monitoring time; Determine the renal injury risk index of each target patient at the first monitoring as a first index, the renal injury risk index at the current monitoring as a second index, and use the ratio of the first index to the second index as a second recovery trend index; The first recovery trend index and the second recovery trend index are combined to determine the fluid rehydration effectiveness index corresponding to the target patient during the current monitoring.

6. A medical resource allocation system for combat casualty rescue according to claim 5, characterized in that: The first recovery trend index and the second recovery trend index are combined to determine the fluid replacement effectiveness index of the target patient during the current monitoring, including: For any target patient, the product of the first recovery trend index and the second recovery trend index of the target patient at the current monitoring time is calculated, the product is normalized to obtain the normalized value of the product, and the normalized value of the product is used as the fluid replacement effectiveness index of the target patient at the current monitoring time.

7. A medical resource allocation system for combat casualty rescue according to claim 1, characterized in that: Combined with the fluid replacement effectiveness index and renal injury risk index of each target patient during the current monitoring, determine the priority index for each target patient in allocating medical resources during the current monitoring, including: Calculate the average value of the fluid replacement effectiveness index of all target patients at the time of current monitoring, and determine the maximum value of the renal injury risk index of all target patients at the time of current monitoring; For any target patient, the ratio of the average value to the target patient's fluid replacement effectiveness index at the time of the current monitoring is used as the first priority factor for allocating medical resources to the target patient at the time of the current monitoring; Calculate the difference between the maximum value and the renal injury risk index of the target patient at the current monitoring time, perform negative correlation processing on the difference, and use the obtained negative correlation value as the second priority factor for medical resource allocation for the target patient at the current monitoring time; The product of the first priority factor and the second priority factor is calculated, and the product of the two priority factors is normalized to obtain the priority index of the target patient when allocating medical resources during the current monitoring.

8. A medical resource allocation system for combat casualty rescue according to claim 7, characterized in that: After obtaining the priority index of each target patient for medical resource allocation during the current monitoring, it also includes: The priority index of each target patient in the allocation of medical resources during the current monitoring is arranged in descending order to obtain a reference sequence for medical staff to adjust the current medical resources.

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