A risk assessment system for severe infection fused with dynamic changes of body temperature

Abstract

The present application relates to the field of health risk assessment, in particular to a kind of severe infection risk assessment system of fusion body temperature dynamic change.The system first obtains the body temperature data and CRP concentration data of patient at each time, according to the fluctuation of body temperature data in the time domain window of each time, obtain the abnormal degree of body temperature of each time, the time corresponding to the first peak in all body temperature data is taken as turning point, any time after turning point is taken as the time to be analyzed, according to the difference of CRP concentration data of the time to be analyzed and turning point, the difference of body temperature data of the time to be analyzed and turning point, and the abnormal degree of body temperature of the time to be analyzed, obtain the initial infection evaluation value of the time to be analyzed, adjust initial infection evaluation value, obtain real infection evaluation value, based on real infection evaluation value, the infection risk of patient is assessed in real time.The present application can improve the accuracy of infection risk assessment of patient.

Description

Technical Field

[0001] This invention relates to the field of health risk assessment, specifically to a severe infection risk assessment system that integrates dynamic changes in body temperature. Background Technology

[0002] Severe infections are a type of disease in clinical medicine with high mortality and complex course. They are usually caused by pathogens such as bacteria, viruses, and fungi. Early detection and timely intervention are crucial for improving patients' health. At the same time, changes in body temperature are an important physiological indicator of severe infections. Changes in body temperature often reflect the severity of the infection and the progression of the disease. Therefore, by integrating dynamic changes in body temperature, we can accurately assess the infection risk of critically ill patients, which can help relevant personnel to develop more effective treatment strategies and prevent further deterioration of the infection.

[0003] In related technologies, the risk of infection is usually assessed by simply monitoring the patient's body temperature and using changes in body temperature. However, since the rise in a patient's body temperature is affected not only by infectious factors but also by non-infectious factors, existing methods cannot exclude the influence of non-infectious factors on the assessment system by relying solely on a single body temperature indicator, thereby reducing the accuracy of the assessment of the patient's infection risk. Summary of the Invention

[0004] To address the technical problem that existing methods, relying solely on body temperature as a single indicator, cannot eliminate the influence of non-infectious factors on the assessment system, thereby reducing the accuracy of patient infection risk assessment, the present invention aims to provide a severe infection risk assessment system that integrates dynamic changes in body temperature. The specific technical solution adopted is as follows:

[0005] This invention also proposes a severe infection risk assessment system that integrates dynamic changes in body temperature, the system comprising:

[0006] The data acquisition module is used to acquire the patient's body temperature and CRP concentration data at each moment during the monitoring process;

[0007] The abnormal body temperature analysis module is used to take any time as the target time, and obtain the degree of abnormal body temperature at the target time based on the difference between the body temperature data at each time in the time domain window of the target time and the preset body temperature threshold, as well as the fluctuation of the body temperature data at each time in the time domain window.

[0008] The infection risk analysis module is used to take the moment corresponding to the first peak in the body temperature data at all times as the turning point, and any time after the turning point as the time to be analyzed. Based on the differences in CRP concentration data between the time to be analyzed and the turning point, the differences in body temperature data between the time to be analyzed and the turning point, and the degree of abnormality in body temperature at the time to be analyzed, the initial infection assessment value of the time to be analyzed is obtained. Based on the changes in body temperature data and CRP concentration data at each time, the initial infection assessment value of the time to be analyzed is adjusted to obtain the true infection assessment value of the time to be analyzed.

[0009] The risk assessment module is used to assess the patient's infection risk in real time based on the actual infection assessment value at each moment.

[0010] Furthermore, the degree of body temperature abnormality at the target time includes:

[0011] Within the time domain window of the target time, the moment when the body temperature data is greater than the preset body temperature threshold is taken as the high body temperature moment in the time domain window;

[0012] Based on the difference between the body temperature data at the high body temperature moment in the time domain window of the target time and the preset body temperature threshold, the first body temperature abnormality coefficient at the target time is obtained.

[0013] Based on the difference in body temperature data between adjacent time points within the time domain window of the target time, the second body temperature abnormality coefficient at the target time is obtained;

[0014] The first and second abnormal body temperature coefficients are combined and normalized to obtain the degree of abnormal body temperature at the target time.

[0015] Furthermore, the first abnormal body temperature coefficient obtained at the target time includes:

[0016] Within the time domain window of the target time, the difference between the body temperature data at each high body temperature time and the preset body temperature threshold is used as the body temperature deviation value at each high body temperature time.

[0017] The sum of the body temperature deviation values ​​at all high body temperature moments in the time domain window is used as the first body temperature abnormality coefficient at the target moment.

[0018] Furthermore, the second body temperature anomaly coefficient obtained at the target time includes:

[0019] Within the time domain window of the target time, any two adjacent times are taken as an adjacent time group, and the absolute value of the difference between the body temperature data of the two times in each adjacent time group is taken as the body temperature fluctuation value of each adjacent time group.

[0020] The average of the body temperature fluctuation values ​​of all adjacent time groups is used as the second body temperature abnormality coefficient at the target time.

[0021] Furthermore, obtaining the initial infection assessment value at the time to be analyzed includes:

[0022] The degree of CRP response at the time of analysis is obtained based on the differences in CRP concentration data between the time to be analyzed and the turning point, the differences between the time to be analyzed and the turning point, and the degree of body temperature abnormality at the time to be analyzed.

[0023] Based on the difference in body temperature data between the time to be analyzed and the turning point, the degree of CRP response at the time to be analyzed, and the degree of body temperature abnormality, the initial infection assessment value at the time to be analyzed is obtained.

[0024] Furthermore, obtaining the CRP response level at the time of analysis includes:

[0025] The difference between the CRP concentration data at the time of analysis and the turning point is used as the numerator, the difference between the time of analysis and the turning point is used as the denominator, and the ratio is used as the CRP growth rate value at the time of analysis.

[0026] The CRP growth rate and the degree of body temperature abnormality at the time of analysis are combined to obtain the CRP response level at the time of analysis.

[0027] Furthermore, obtaining the initial infection assessment value for the time to be analyzed based on the difference in body temperature data between the time to be analyzed and the turning point, the degree of CRP response at the time to be analyzed, and the degree of body temperature abnormality includes:

[0028] The absolute values ​​of the differences in body temperature data between the time to be analyzed and the turning point are negatively correlated to obtain the body temperature decrease performance value at the time to be analyzed.

[0029] The body temperature decrease, CRP response, and abnormal body temperature at the time of analysis are combined and normalized to obtain the initial infection assessment value at the time of analysis.

[0030] Furthermore, obtaining the true infection assessment value at the time of analysis includes:

[0031] The point at which the body temperature data rises and the CRP concentration data falls is used as the reference point;

[0032] Based on the formula for calculating the adjusted weights, the adjusted weights at the time to be analyzed are obtained. The formula for calculating the adjusted weights is as follows:

[0033]

[0034] in, Indicates the adjusted weights for the time interval to be analyzed; This represents the first peak value in the CRP concentration data across all time points; This represents the CRP concentration data at the time of analysis. This represents the initial infection assessment value at the time of analysis. This represents the initial infection assessment value at the time preceding the time to be analyzed. Indicates the initial infection assessment value at the reference time; This represents the body temperature data at the time of analysis. This represents the body temperature data from the time preceding the time to be analyzed. Body temperature data at a reference time; This represents the preset adjustment coefficient, with a value range of [value range missing]. ; Represents the normalization function;

[0035] Based on the adjusted weights at the time to be analyzed, the initial infection assessment value at the time to be analyzed is adjusted to obtain the true infection assessment value at the time to be analyzed.

[0036] Further, adjusting the initial infection assessment value at the time to be analyzed based on the adjusted weights to obtain the true infection assessment value at the time to be analyzed includes:

[0037] The product of the adjusted weight and the initial infection assessment value at the time to be analyzed is used as the adjustment amount of the assessment value at the time to be analyzed.

[0038] The difference between the initial infection assessment value and the adjusted assessment value at the time to be analyzed is taken as the true infection assessment value at the time to be analyzed.

[0039] Furthermore, the real-time assessment of the patient's infection risk includes:

[0040] For any time after the turning point, if the actual infection assessment value at that time is not greater than the preset first assessment threshold, then the patient has a primary infection risk.

[0041] If the actual infection assessment value at that moment is greater than a preset first assessment threshold but not greater than a preset second assessment threshold, then the patient has an intermediate risk of infection.

[0042] If the actual infection assessment value at that moment is greater than the preset second assessment threshold, then the patient has a high risk of infection, wherein the severity of primary infection risk, intermediate infection risk and high infection risk increases progressively.

[0043] The present invention has the following beneficial effects:

[0044] This invention addresses the limitation of existing methods that rely solely on body temperature as a single indicator, which fails to eliminate the influence of non-infectious factors on the assessment system and thus reduces the accuracy of patient infection risk assessment. Therefore, it first acquires the patient's body temperature and CRP concentration data at each moment. When a critically ill patient develops an infection at a certain time, the body will experience an inflammatory response, resulting in fever and elevated body temperature. This leads to abnormally high and fluctuating body temperature data at various moments within that local timeframe. Therefore, the degree of temperature abnormality can reflect the extent of the patient's abnormal body temperature at the target time. This invention also considers that the increase in patient body temperature is not only influenced by infectious factors but also by non-infectious factors such as medications. The influence of infectious factors makes it impossible to accurately assess a patient's infection risk solely based on the degree of abnormal body temperature. Considering that the concentration of C-reactive protein (CRP) is elevated in patients under infectious conditions, and also considering that CRP concentration may be elevated in non-infectious conditions, its specificity is insufficient. Therefore, this invention performs correlation analysis on body temperature data and CRP concentration data. The initial infection assessment value obtained initially reflects the probability of infection in the patient at the time of analysis. The initial infection assessment value is further adjusted, and the actual infection assessment value obtained accurately reflects the probability of infection in the patient at the time of analysis, thereby enabling real-time assessment of the patient's infection risk and improving the accuracy of infection risk assessment. Attached Figure Description

[0045] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 A block diagram of a severe infection risk assessment system that integrates dynamic changes in body temperature, provided as an embodiment of the present invention;

[0047] Figure 2 The figure shows the change curves of patient body temperature and CRP concentration data provided in one embodiment of the present invention. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a severe infection risk assessment system integrating dynamic body temperature changes proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, 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 pertains.

[0050] The following description, in conjunction with the accompanying drawings, details a specific scheme for a severe infection risk assessment system that integrates dynamic changes in body temperature, provided by this invention.

[0051] Please see Figure 1 The diagram illustrates a block diagram of a severe infection risk assessment system based on dynamic changes in body temperature, according to an embodiment of the present invention. The system includes: a data acquisition module 101, an abnormal body temperature analysis module 102, an infection risk analysis module 103, and a risk assessment module 104.

[0052] The data acquisition module 101 is used to acquire the patient's body temperature and CRP concentration data at each moment during the monitoring process.

[0053] When critically ill patients develop infections such as lung infections, they may experience fever, leading to abnormally high body temperatures. At the same time, other physiological indicators in the patient's body, such as the concentration of C-reactive protein (CRP), will also increase.

[0054] Therefore, in this embodiment of the invention, the patient first wears a smart bracelet or other temperature monitoring device to collect the patient's temperature data at each moment. At the same time, the patient's serum or plasma sample is extracted, and after centrifugation, the patient's CRP concentration data, i.e., C-reactive protein concentration data, is collected at each moment. The time interval for collecting the temperature data and the CRP concentration data is the same. In one embodiment of the invention, the data collection time interval is set to 1 hour. The data collection time interval can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0055] Please see Figure 2 The figure shows a graph of changes in a patient's body temperature and CRP concentration data provided in an embodiment of the present invention.

[0056] The abnormal body temperature analysis module 102 is used to take any time as the target time, and obtain the degree of abnormal body temperature at the target time based on the difference between the body temperature data at each time in the time domain window of the target time and the preset body temperature threshold, as well as the fluctuation of the body temperature data at each time in the time domain window.

[0057] When a critically ill patient develops an infection at a certain moment, the patient's body will experience an inflammatory response, resulting in fever and elevated body temperature. This leads to excessively high body temperature data at any given moment, exceeding the upper limit of normal body temperature, and exhibiting significant fluctuations within that localized timeframe. Therefore, this embodiment of the invention first analyzes any given moment as the target moment, comparing the body temperature data at each moment within the time-domain window of the target moment with the preset body temperature threshold, and analyzing the fluctuations in body temperature data at each moment within the time-domain window. The obtained degree of body temperature abnormality reflects the patient's body temperature within the target range. The degree of abnormality at the target time can be used to accurately assess the patient's infection risk based on the degree of body temperature abnormality. The length of the time domain window for the target time is set to 5, which means that the time domain window includes the four other times closest to the target time and the target time itself. The preset body temperature threshold is usually in the range of 36.8~37.5 degrees Celsius. When it is greater than the preset body temperature threshold, it can be considered that a fever has occurred. In one embodiment of the present invention, the preset body temperature threshold is set to 37.2 degrees Celsius. The specific length of the time domain window and the specific value of the preset body temperature threshold can also be set by the implementer according to the specific implementation scenario, and are not limited here.

[0058] Preferably, in one embodiment of the present invention, the method for obtaining the degree of body temperature abnormality at a target time specifically includes:

[0059] First, within the time domain window of the target time, the moments when the body temperature data is greater than the preset body temperature threshold are defined as the high body temperature moments in the time domain window. The more high body temperature moments there are in the time domain window, and the greater the difference between the body temperature data of the high body temperature moments and the preset body temperature threshold, the more abnormal the body temperature data is in a local period of the target time. Therefore, the first abnormal body temperature coefficient of the target time can be obtained based on the difference between the body temperature data of the high body temperature moments in the time domain window of the target time and the preset body temperature threshold.

[0060] Preferably, in one embodiment of the present invention, the method for obtaining the first body temperature anomaly coefficient at the target time specifically includes:

[0061] Within the time domain window of the target time, the difference between the body temperature data at each high body temperature moment and the preset body temperature threshold is used as the body temperature deviation value at each high body temperature moment. The larger the body temperature deviation value, the greater the body temperature data at the high body temperature moment is compared with the preset body temperature threshold, and the more abnormal the body temperature data in the local period of the target time is. In this way, the cumulative value of the body temperature deviation values ​​of all high body temperature moments in the time domain window can be used as the first body temperature abnormality coefficient at the target time.

[0062] As an example, in one embodiment of the present invention, the expression for the first body temperature anomaly coefficient at the target time can be specifically as follows:

[0063]

[0064] in, Indicates the first abnormal body temperature coefficient at the target time; The first time in the time domain window representing the target time Body temperature data at each moment of high body temperature; This indicates the preset body temperature threshold; Represents the first in the time-domain window Temperature deviation at each high temperature moment; This indicates the number of times the body temperature is high within the time-domain window.

[0065] The greater the difference between the body temperature data at adjacent moments in the time domain window, the more obvious the fluctuation of the body temperature data in the time domain window is in the time series. In this case, the body temperature data at the target moment is more abnormal. Therefore, the second body temperature abnormality coefficient at the target moment is obtained based on the difference between the body temperature data at adjacent moments in the time domain window of the target moment.

[0066] Preferably, in one embodiment of the present invention, the method for obtaining the second body temperature anomaly coefficient at the target time specifically includes:

[0067] Within the time domain window of the target time, any two adjacent time points are considered as an adjacent time point group. The absolute value of the difference between the body temperature data of the two time points in each adjacent time point group is taken as the body temperature fluctuation value of each adjacent time point group. The larger the body temperature fluctuation value, the more obvious the fluctuation of the body temperature data between two adjacent time points. Therefore, the average value of the body temperature fluctuation values ​​of all adjacent time point groups can be taken as the second body temperature abnormality coefficient of the target time.

[0068] As an example, in one embodiment of the present invention, the expression for the second body temperature anomaly coefficient at the target time can be specifically as follows:

[0069]

[0070] in, The second body temperature anomaly coefficient represents the target time. and These represent the first time domain window of the target time. Body temperature data from two times within a group of adjacent time points; The first time in the time domain window representing the target time Body temperature fluctuation values ​​of adjacent time groups; This represents the number of adjacent time groups within the time domain window of the target time.

[0071] Then, the first and second abnormal body temperature coefficients are combined and normalized to limit the calculation results to within a certain range. Within a certain range, the degree of abnormal body temperature at the target time can be obtained.

[0072] In embodiments of the present invention, the sum or product of the first and second body temperature abnormality coefficients can be calculated to achieve a comprehensive analysis of the two, which is not limited herein.

[0073] In one embodiment of the present invention, the normalization process can be specifically, for example, maximum and minimum value normalization. Furthermore, the normalization in subsequent steps can all adopt maximum and minimum value normalization. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of the numerical values, which will not be elaborated further.

[0074] As an example, in one embodiment of the present invention, the expression for the degree of body temperature abnormality at the target time can be specifically as follows:

[0075]

[0076] in, Indicates the degree of abnormality in body temperature at the target time; Indicates the first abnormal body temperature coefficient at the target time; The second body temperature anomaly coefficient represents the target time. This represents the normalization function, used for normalization processing.

[0077] The degree of body temperature abnormality at each moment can be obtained using the same method described above.

[0078] The infection risk analysis module 103 is used to take the moment corresponding to the first peak of body temperature data at all times as the turning point, and any time after the turning point as the time to be analyzed. Based on the difference in CRP concentration data between the time to be analyzed and the turning point, the difference in body temperature data between the time to be analyzed and the turning point, and the degree of abnormality in body temperature at the time to be analyzed, the initial infection assessment value of the time to be analyzed is obtained. Based on the changes in body temperature data and CRP concentration data at each time, the initial infection assessment value of the time to be analyzed is adjusted to obtain the true infection assessment value of the time to be analyzed.

[0079] Fever is an early symptom of infection in patients. Cytokines act on the hypothalamus's thermoregulatory center, causing a rapid rise in body temperature. This then stimulates the liver to produce C-reactive protein (CRP), leading to an increase in CRP concentration in patients. However, due to the lack of specificity of CRP, it may also rise in non-infectious states, affecting the accuracy of infection risk assessment in critically ill patients. Therefore, it is necessary to perform correlation analysis between patients' body temperature data and CRP concentration data. Furthermore, considering that when a patient exhibits signs of infection, the timing of changes in CRP concentration is relatively delayed compared to changes in body temperature data, meaning that the rise in CRP concentration begins later than the rise in body temperature (usually when body temperature first reaches its peak), this embodiment of the invention first extracts the first peak value from all body temperature data. The peak value can be extracted using existing derivative methods, which will not be elaborated here. The moment corresponding to the first peak value is taken as the turning point. Then, infection risk assessment is performed on any moment after the turning point, and any moment after the turning point is taken as the moment to be analyzed.

[0080] When a patient's CRP concentration data shows an upward trend after the inflection point, and the more significant the upward trend, the more significant the patient's C-reactive protein response. At the same time, the smaller the decrease in the patient's body temperature data after the inflection point, the more likely the patient is to have a more serious infection risk. Therefore, we analyzed the differences in CRP concentration data between the time to be analyzed and the inflection point, and the differences in body temperature data between the time to be analyzed and the inflection point. In addition, we combined the degree of abnormal body temperature at the time to be analyzed, and used the obtained initial infection assessment value to preliminarily reflect the patient's possibility of infection at the time to be analyzed.

[0081] Preferably, in one embodiment of the present invention, the method for obtaining the initial infection assessment value at the time to be analyzed specifically includes:

[0082] First, based on the differences in CRP concentration data between the time to be analyzed and the turning point, the differences between the time to be analyzed and the turning point, and the degree of body temperature abnormality at the time to be analyzed, the degree of CRP response at the time to be analyzed is obtained. The greater the degree of CRP response, the more obvious the response of C-reactive protein in the patient's body after the body temperature rises at the time to be analyzed, which indicates that the patient is more likely to have an infection risk at the time to be analyzed. Subsequently, the initial infection assessment value at the time to be analyzed can be accurately calculated based on the degree of CRP response.

[0083] Preferably, in one embodiment of the present invention, the method for obtaining the CRP response level at the time to be analyzed specifically includes:

[0084] The difference in CRP concentration data between the time to be analyzed and the turning point is used as the numerator, and the difference between the time to be analyzed and the turning point is used as the denominator. The ratio is taken as the CRP growth rate value at the time to be analyzed. The larger the CRP growth rate value, the more obvious the upward trend of C-reactive protein at the time to be analyzed. At the same time, the greater the degree of body temperature abnormality at the time to be analyzed, the more significant the patient's C-reactive protein response at the time to be analyzed. Therefore, the CRP growth rate value and the degree of body temperature abnormality at the time to be analyzed can be combined to obtain the degree of CRP response at the time to be analyzed.

[0085] In embodiments of the present invention, the sum or product of the CRP growth rate and the degree of body temperature abnormality at the time to be analyzed can be used as the CRP response level at the time to be analyzed, thereby achieving a comprehensive analysis of the two, which is not limited here.

[0086] As an example, in one embodiment of the present invention, the expression for the CRP response level at the time to be analyzed can be specifically as follows:

[0087]

[0088] in, This indicates the degree of CRP response at the time of analysis; This represents the CRP concentration data at the time of analysis. CRP concentration data indicating the turning point; Indicates the time to be analyzed. Indicating a turning point, then This indicates the length between the moment to be analyzed and the turning point; This represents the CRP growth rate at the time of analysis. This indicates the degree of abnormality in body temperature at the time of analysis.

[0089] Then, the greater the CRP response and the greater the abnormal body temperature at the time of analysis, the lower the body temperature data at the time of analysis compared to the turning point, indicating that the patient's body temperature is still high at the time of analysis, and the patient is likely to be at risk of infection. Therefore, the initial infection assessment value at the time of analysis can be obtained based on the difference in body temperature data between the time of analysis and the turning point, the CRP response and the abnormal body temperature at the time of analysis.

[0090] Preferably, in one embodiment of the present invention, the method for obtaining the initial infection assessment value at the time to be analyzed further includes:

[0091] The absolute values ​​of the differences in body temperature data between the time point to be analyzed and the turning point are negatively correlated to obtain the body temperature drop performance value at the time point to be analyzed. A larger body temperature drop performance value indicates that the body temperature data at the time point to be analyzed is smaller relative to the turning point, suggesting that the patient's body temperature remained at a relatively high level at the time point to be analyzed. If the CRP response and body temperature abnormality are also significant at the time point to be analyzed, it indicates that the patient is more likely to be at risk of infection at that time. Therefore, the body temperature drop performance value, CRP response, and body temperature abnormality at the time point to be analyzed can be combined and normalized to limit the calculation results to a range of values. Within the range, thus obtaining the initial infection assessment value at the time to be analyzed.

[0092] In embodiments of the present invention, the sum or product of the body temperature drop performance value, CRP response degree and body temperature abnormality degree at the time to be analyzed can be used to achieve a comprehensive analysis of the three factors, which is not limited herein.

[0093] As an example, in one embodiment of the present invention, the expression for the initial infection assessment value at the time to be analyzed can be specifically as follows:

[0094]

[0095] in, This represents the initial infection assessment value at the time of analysis. This represents the body temperature data at the time of analysis. Temperature data indicating a turning point; This indicates the temperature drop at the time of analysis. This indicates the degree of CRP response at the time of analysis; Indicates the degree of abnormality in body temperature at the time of analysis; This represents the normalization function, used for normalization processing; This indicates a preset adjustment parameter used to prevent the denominator from being 0. The range of values ​​is In one embodiment of the present invention, the following is used: Set to 0.01, The specific values ​​can be set by the implementer according to the specific implementation scenario, and are not limited here.

[0096] Using the same method described above, the initial infection assessment value can be obtained for each time point after the turning point. After the turning point, if the initial infection assessment value continues to increase, it indicates that the patient's infection condition is continuously deteriorating. At this time, medication or treatment may be necessary. The patient's body temperature and CRP concentration data will show a relative decrease. However, when the treatment effect is weak, the decrease will be followed by an increase, indicating that the condition is deteriorating or the current treatment effect is weak, which means that the risk of infection is increasing. When the CRP concentration data and body temperature data decrease together, it can reflect that the current infection is under control to a certain extent.

[0097] A decrease in CRP concentration data may reflect a reduced risk of infection, but an increase in body temperature still needs to be assessed in conjunction with other factors. For example, if the patient is receiving antibiotic treatment, a decrease in CRP concentration data may indicate that the treatment is effective and the infection is under control, while an increase in body temperature may be due to other non-infectious factors such as drug fever. The body temperature will return to normal after the medication is discontinued. Therefore, in this case, the patient's actual infection risk assessment value should be relatively low. Therefore, in this embodiment of the invention, the initial infection assessment value at the time of analysis is adjusted according to the changes in body temperature data and CRP concentration data at each time point, so as to obtain the true infection assessment value at the time of analysis. Subsequently, the infection risk of the patient can be more accurately assessed based on the true infection assessment value.

[0098] Preferably, in one embodiment of the present invention, the method for obtaining the true infection assessment value at the time to be analyzed specifically includes:

[0099] Use the intersection of the rising body temperature data and the falling CRP concentration data as the reference time. Figure 2 Where point Y is the intersection of the rising body temperature data and the falling CRP concentration data, the time T corresponding to point Y is the reference time.

[0100] Based on the formula for calculating the adjusted weights, the adjusted weights at the time to be analyzed are obtained. The formula for calculating the adjusted weights is as follows:

[0101]

[0102] in, Indicates the adjusted weights for the time interval to be analyzed; This represents the first peak value among all CRP concentration data at all times. The method for obtaining this value is the same as the method for obtaining the first peak value of the body temperature data mentioned above. This represents the CRP concentration data at the time of analysis. This represents the initial infection assessment value at the time of analysis. This represents the initial infection assessment value at the time preceding the time to be analyzed. Indicates the initial infection assessment value at the reference time; This represents the body temperature data at the time of analysis. This represents the body temperature data from the time preceding the time to be analyzed. Body temperature data at a reference time; This represents a preset adjustment coefficient, used to prevent the denominator from being 0. The range of values ​​is In one embodiment of the present invention, the following is used: Set to 0.01, The specific values ​​can be set by the implementer according to the specific implementation scenario, and are not limited here; This represents the normalization function, used for normalization processing.

[0103] Specifically, after the first peak in CRP concentration data, the difference between the CRP concentration data at the time of analysis and its first peak is considered. The larger the value, the greater the adjustment should be made to the initial infection assessment value at the time of analysis. The larger the value, the faster the initial infection assessment value decreases compared to the body temperature data. This means the decrease in CRP concentration offsets and exceeds the change in body temperature, making it more likely that the high body temperature is caused by other non-infectious factors. Therefore, a greater adjustment to the initial infection assessment value at the time of analysis is needed, i.e., a larger adjustment weight at the time of analysis. The larger it is.

[0104] The greater the adjustment weight of the time to be analyzed, the greater the degree of adjustment required to the initial infection assessment value of the time to be analyzed. Therefore, the initial infection assessment value of the time to be analyzed can be adjusted according to the adjustment weight of the time to be analyzed to obtain the true infection assessment value of the time to be analyzed.

[0105] Preferably, in one embodiment of the present invention, the method for obtaining the true infection assessment value at the time to be analyzed further includes:

[0106] The above analysis shows that the patient's actual infection risk assessment value at the time of analysis is smaller than the initial infection risk assessment value. Therefore, it is necessary to appropriately reduce the initial infection assessment value at the time of analysis. Thus, the product of the adjustment weight at the time of analysis and the initial infection assessment value can be used as the adjustment amount of the assessment value at the time of analysis, and the difference between the initial infection assessment value at the time of analysis and the adjustment amount of the assessment value can be used as the true infection assessment value at the time of analysis.

[0107] As an example, in one embodiment of the present invention, the expression for the true infection assessment value at the time to be analyzed can be specifically as follows:

[0108]

[0109] in, This represents the actual infection assessment value at the time of analysis; This represents the initial infection assessment value at the time of analysis. Indicates the adjusted weights for the time interval to be analyzed; This indicates the adjustment amount of the evaluation value at the time to be analyzed.

[0110] The same method described above can be used to obtain the true infection assessment value for each time point after the turning point.

[0111] The risk assessment module 104 is used to assess the patient's infection risk in real time based on the actual infection assessment value at each moment.

[0112] The real infection assessment value obtained through the above process can more accurately assess the patient's infection risk. Furthermore, for any point after the turning point, the higher the real infection assessment value at that moment, the greater the risk of infection for the patient at that moment. Therefore, the patient's infection risk can be assessed in real time based on the real infection assessment value at each moment, thereby improving the accuracy of the patient's infection risk assessment.

[0113] Preferably, in one embodiment of the present invention, the method for obtaining the true infection assessment value at the time to be analyzed further includes:

[0114] For any point after the turning point, if the actual infection assessment value at that point is not greater than the preset first assessment threshold, then the patient has a primary infection risk.

[0115] If the actual infection assessment value at that moment is greater than the preset first assessment threshold but not greater than the preset second assessment threshold, then the patient has an intermediate risk of infection.

[0116] If the actual infection assessment value at that moment is greater than the preset second assessment threshold, the patient has a high risk of infection, with the severity of primary, intermediate and high infection risks increasing progressively.

[0117] The preset range of the first evaluation threshold is as follows: The preset range of the second evaluation threshold is: In one embodiment of the present invention, the preset first evaluation threshold is set to 0.3 and the preset second evaluation threshold is set to 0.7. The specific values ​​of the preset first evaluation threshold and the preset second evaluation threshold can also be set by the implementer according to the specific implementation scenario, and are not limited here.

[0118] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0119] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A severe infection risk assessment system integrating dynamic changes in body temperature, characterized in that, The system includes: The data acquisition module is used to acquire the patient's body temperature and CRP concentration data at each moment during the monitoring process; The abnormal body temperature analysis module is used to take any time as the target time, and obtain the degree of abnormal body temperature at the target time based on the difference between the body temperature data at each time in the time domain window of the target time and the preset body temperature threshold, as well as the fluctuation of the body temperature data at each time in the time domain window. The infection risk analysis module is used to take the moment corresponding to the first peak of body temperature data at all times as the turning point, and any time after the turning point as the time to be analyzed. Based on the differences in CRP concentration data between the time to be analyzed and the turning point, the differences in body temperature data between the time to be analyzed and the turning point, and the degree of abnormality in body temperature at the time to be analyzed, the initial infection assessment value for the time to be analyzed is obtained. Based on the changes in body temperature data and CRP concentration data at each time, the initial infection assessment value for the time to be analyzed is adjusted to obtain the true infection assessment value for the time to be analyzed. The time corresponding to the intersection of the rising body temperature data and the falling CRP concentration data is used as the reference time. Based on the formula for calculating the adjusted weights, the adjusted weights at the time to be analyzed are obtained. The formula for calculating the adjusted weights is as follows: in, Indicates the adjusted weights for the time interval to be analyzed; This represents the first peak value in the CRP concentration data across all time points; This represents the CRP concentration data at the time of analysis. This represents the initial infection assessment value at the time of analysis. This represents the initial infection assessment value at the time preceding the time to be analyzed. Indicates the initial infection assessment value at the reference time; This represents the body temperature data at the time of analysis. This represents the body temperature data from the time preceding the time to be analyzed. Body temperature data at a reference time; This represents the preset adjustment coefficient, with a value range of [value range missing]. ; Represents the normalization function; The product of the adjusted weight and the initial infection assessment value at the time to be analyzed is used as the adjustment amount of the assessment value at the time to be analyzed. The difference between the initial infection assessment value and the adjustment amount of the assessment value at the time to be analyzed is taken as the true infection assessment value at the time to be analyzed. The risk assessment module is used to assess the patient's infection risk in real time based on the actual infection assessment value at each moment.

2. The severe infection risk assessment system integrating dynamic changes in body temperature as described in claim 1, characterized in that, The degree of abnormal body temperature at the target time includes: Within the time domain window of the target time, the moment when the body temperature data is greater than the preset body temperature threshold is taken as the high body temperature moment in the time domain window; Based on the difference between the body temperature data at the high body temperature moment in the time domain window of the target time and the preset body temperature threshold, the first body temperature abnormality coefficient at the target time is obtained. Based on the difference in body temperature data between adjacent time points within the time domain window of the target time, the second body temperature abnormality coefficient at the target time is obtained; The first and second abnormal body temperature coefficients are combined and normalized to obtain the degree of abnormal body temperature at the target time.

3. The severe infection risk assessment system integrating dynamic changes in body temperature according to claim 2, characterized in that, The first abnormal body temperature coefficient obtained at the target time includes: Within the time domain window of the target time, the difference between the body temperature data at each high body temperature moment and the preset body temperature threshold is used as the body temperature deviation value at each high body temperature moment. The sum of the body temperature deviation values ​​at all high body temperature moments in the time domain window is used as the first body temperature abnormality coefficient at the target moment.

4. The severe infection risk assessment system integrating dynamic changes in body temperature according to claim 2, characterized in that, The second body temperature anomaly coefficient obtained at the target time includes: Within the time domain window of the target time, any two adjacent times are taken as an adjacent time group, and the absolute value of the difference between the body temperature data of the two times in each adjacent time group is taken as the body temperature fluctuation value of each adjacent time group. The average of the body temperature fluctuation values ​​of all adjacent time groups is used as the second body temperature abnormality coefficient at the target time.

5. The severe infection risk assessment system integrating dynamic changes in body temperature according to claim 1, characterized in that, The initial infection assessment value obtained at the time to be analyzed includes: The degree of CRP response at the time of analysis is obtained based on the differences in CRP concentration data between the time to be analyzed and the turning point, the differences between the time to be analyzed and the turning point, and the degree of body temperature abnormality at the time to be analyzed. Based on the difference in body temperature data between the time to be analyzed and the turning point, the degree of CRP response at the time to be analyzed, and the degree of body temperature abnormality, the initial infection assessment value at the time to be analyzed is obtained.

6. The severe infection risk assessment system integrating dynamic changes in body temperature according to claim 5, characterized in that, The degree of CRP response at the time of analysis includes: The difference between the CRP concentration data at the time of analysis and the turning point is used as the numerator, the difference between the time of analysis and the turning point is used as the denominator, and the ratio is used as the CRP growth rate value at the time of analysis. The CRP growth rate and the degree of body temperature abnormality at the time of analysis are combined to obtain the CRP response level at the time of analysis.

7. The severe infection risk assessment system integrating dynamic changes in body temperature according to claim 5, characterized in that, The process of obtaining the initial infection assessment value for the time to be analyzed based on the difference in body temperature data between the time to be analyzed and the turning point, the degree of CRP response at the time to be analyzed, and the degree of body temperature abnormality includes: The absolute values ​​of the differences in body temperature data between the time to be analyzed and the turning point are negatively correlated to obtain the body temperature decrease performance value at the time to be analyzed. The body temperature decrease, CRP response, and abnormal body temperature at the time of analysis are combined and normalized to obtain the initial infection assessment value at the time of analysis.

8. The severe infection risk assessment system integrating dynamic changes in body temperature according to claim 1, characterized in that, The real-time assessment of the patient's infection risk includes: For any time after the turning point, if the actual infection assessment value at that time is not greater than the preset first assessment threshold, then the patient has a primary infection risk. If the actual infection assessment value at that moment is greater than a preset first assessment threshold but not greater than a preset second assessment threshold, then the patient has an intermediate risk of infection. If the actual infection assessment value at that moment is greater than the preset second assessment threshold, then the patient has a high risk of infection, wherein the severity of primary infection risk, intermediate infection risk and high infection risk increases progressively.

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