Traumatic hemorrhage risk assessment method and system

Abstract

The invention belongs to the technical field of risk assessment, and particularly relates to a traumatic hemorrhage risk assessment method and system, and the method comprises the steps: obtaining pupil reaction data of a patient, and determining a basic state value of pupil reaction based on the pupil reaction data; adjusting ambient light intensity according to the basic state value, and monitoring pupil reaction change after the ambient light intensity is adjusted; an abnormal fluctuation interval is recognized according to the pupil reaction change condition, and the abnormal fluctuation interval is compared with a preset safety threshold value; predicting the blood loss degree according to the comparison result, and evaluating the shock risk in combination with the predicted blood loss degree. By recording and analyzing pupil reaction changes of a patient under different illumination conditions, determining a basic state value and identifying an abnormal fluctuation interval, the blood loss degree is predicted and the shock risk is evaluated, and the method not only can quickly obtain data required by evaluation and reduce diagnosis time, but also can improve the evaluation accuracy and improve the diagnosis efficiency. Therefore, a more reliable decision basis is provided for emergency doctors.

Description

Technical Field

[0001] The present invention belongs to the technical field of risk assessment, and in particular relates to a method and system for assessing the risk of traumatic blood loss. Background Art

[0002] Traumatic blood loss is a common emergency in emergency medicine. Rapid and accurate assessment of a patient's blood loss severity and risk of shock is crucial for timely and appropriate treatment. Existing methods for assessing the risk of traumatic blood loss primarily rely on clinical symptoms, vital sign monitoring, and laboratory testing. These methods typically include observing indicators such as the patient's blood pressure, heart rate, respiratory rate, and state of consciousness, combined with hematological tests (such as hemoglobin concentration) for comprehensive assessment.

[0003] However, traditional assessment methods have limitations. First, these methods often require a long time to obtain results; for example, hematological tests require waiting for laboratory analysis results. Second, many indicators may not be obvious in the early stages, leading to delayed diagnosis and treatment. Furthermore, the large individual differences between patients make it difficult for a single physiological parameter to fully reflect the extent of blood loss and the risk of shock. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for assessing the risk of traumatic blood loss, which can not only quickly obtain the data required for the assessment and reduce the diagnosis time, but also improve the accuracy of the assessment, thereby providing emergency physicians with a more reliable decision-making basis, and solving the problem of how to use a non-invasive and rapid method to predict the patient's blood loss degree and shock risk in the traumatic blood loss risk assessment.

[0005] To achieve the above objectives, the present invention provides a method for assessing the risk of traumatic blood loss, comprising the following steps: The patient's pupillary response data is obtained under different lighting conditions, and a basal state value of the pupillary response is determined based on the pupillary response data; the ambient light intensity is adjusted according to the basal state value, and changes in the pupillary response after the adjustment of the ambient light intensity are monitored; abnormal fluctuation intervals are identified based on the changes in the pupillary response, and the abnormal fluctuation intervals are compared with a preset safety threshold; the comparison results are used to predict the degree of blood loss, and the risk of shock is assessed based on the predicted degree of blood loss.

[0006] Preferably, obtaining the patient's pupil response data under different lighting conditions includes: Record the initial pupil diameter D1 under the initial ambient lighting conditions; Adjust the ambient light intensity to the preset value and wait for a period of stabilization time T1; Measure the pupil diameter D2 after the stabilization time T1; Based on the pupil diameter at the initial time and after adjusting for ambient lighting, the pupil contraction rate R to the change in lighting is calculated, where R = (D1-D2) / D1*100%.

[0007] Preferably, determining the pupillary response base state value based on the pupillary response data includes: Select the average value M of pupil diameter in N consecutive measurements; Calculate the difference D_diff_i between each measurement value and the average value M, where i is the number of measurements, and find the sum of the squares S of all the differences D_diff_i, where S=∑(D_diff_i)^2; Combining the mean and the sum of squares, a basic state value BSV that can reflect the stability of pupil response is calculated, where BSV=M-√(S / N).

[0008] Preferably, adjusting the ambient light intensity according to the basic state value includes: Determine the target light intensity L0 based on the basic state value and the preset coefficient, where L0=BSV*k, k is the preset coefficient; Gradually increase or decrease the current ambient light intensity to the target light intensity L0, and record the pupil diameter PD_adj_j after each change, where j represents the number of adjustments; Calculate the difference ΔPD_adj_j between the pupil diameter after each adjustment and the basic state value BSV, where ΔPD_adj_j=|PD_adj_j-BSV|, and obtain the average value AVG_ΔPD_adj of all differences ΔPD_adj_j, where AVG_ΔPD_adj=∑ΔPD_adj_j / N, N is the number of adjustments, and use the AVG_ΔPD_adj as the evaluation standard for the final adjustment result.

[0009] Preferably, monitoring pupillary response changes after adjusting ambient light intensity includes: First, ensure that the ambient light has been adjusted to the target light intensity L0, and wait for a stable period T_stable to ensure that the pupil is fully adapted to the new lighting conditions; The pupil diameter PD_L0 at the end of the stable period T_stable was recorded, and the pupil diameter PD_n was repeatedly measured at fixed time intervals ΔT, where n represents the number of measurements; Calculate the pupil diameter change rate CR_n for each measurement, where CR_n=(PD_n-PD_L0) / PD_L0*100%, and calculate the average value AVG_CR of all change rates, where AVG_CR=∑CR_n / M, where M is the number of measurements.

[0010] Preferably, identifying the abnormal fluctuation interval based on changes in pupillary response includes: Setting a fluctuation threshold WT based on the average change rate AVG_CR and a preset coefficient t; Compare the pupil diameter change rate CR_n measured each time with the fluctuation threshold WT, and mark all time periods greater than the fluctuation threshold WT as potential abnormal intervals PAI_j, where j represents the jth potential abnormal interval; Calculate the standard deviation SD_PA of pupil diameter change rate within each potential abnormal interval PAI_j, where , N is the number of measurements within the interval, and the PAI_j whose standard deviation exceeds the preset standard deviation threshold SDT is confirmed as the abnormal fluctuation interval AWI.

[0011] Preferably, comparing the abnormal fluctuation range with a preset safety threshold includes: A safety threshold ST is set based on the average change rate AVG_CR and a preset coefficient u, where ST = AVG_CR * u, and u is the preset coefficient; For each abnormal fluctuation interval AWI, calculate the average value AVG_AWI of the pupil diameter change rate within the interval; Compare the average value AVG_AWI of each abnormal fluctuation interval AWI with the safety threshold ST; All abnormal fluctuation intervals where the average value AVG_AWI exceeds the safety threshold ST are marked as high-risk intervals HRI_v, where v represents the vth high-risk interval, and the duration T_HRI of the HRI_v is recorded.

[0012] Preferably, the method of predicting the degree of blood loss using the comparison results includes: The blood loss degree coefficient BLC is set based on the duration of the high-risk interval and the weight coefficient v, where BLC=∑T_HRIv, v is the weight coefficient of each high-risk interval HRI; Calculate the average pupil diameter change rate AVG_HRI of all high-risk intervals HRI_v, where AVG_HRI=∑AVG_AWI / V, V is the total number of high-risk intervals; Combining the blood loss degree coefficient BLC with the average pupil diameter change rate AVG_HRI to generate a comprehensive evaluation value CEV, where CEV=BLCAVG_HRI; The comprehensive evaluation value CEV is compared with a preset blood loss level threshold BLT to determine the patient's blood loss level.

[0013] Preferably, the step of assessing shock risk in combination with the predicted degree of blood loss comprises: The shock risk coefficient SRC is set based on the comprehensive evaluation value CEV and the preset coefficient w, where SRC = CEV*w, w is the preset coefficient. Based on the patient's comprehensive evaluation value CEV, the basic shock risk level BLR is determined, where BLR is the preset level corresponding to CEV; Calculate the shock risk modification value SRM, where SRM=SRC+BLR. The modified shock risk value SRM is generated by combining the shock risk coefficient SRC and the basic shock risk level BLR. The shock risk modification value SRM is compared with the preset shock risk threshold SRT to determine the patient's shock risk level.

[0014] In another aspect, the present invention provides a traumatic blood loss risk assessment system, comprising: Pupil response data acquisition module, used to obtain patient pupil response data under different lighting conditions; a basic state value determination module, configured to determine a basic state value of pupil reaction based on the pupil reaction data; an ambient light adjustment module, configured to adjust the ambient light intensity according to the basic state value; Pupil response monitoring module, used to monitor pupil response changes after adjusting the ambient light intensity; An abnormal fluctuation interval recognition module is used to identify abnormal fluctuation intervals based on changes in pupil response; A safety threshold comparison module is used to compare the abnormal fluctuation range with a preset safety threshold; A blood loss degree prediction module, used to predict the blood loss degree using the comparison results; The shock risk assessment module is used to assess the risk of shock based on the predicted degree of blood loss.

[0015] Technical effects and advantages of the present invention: Compared with the existing technology, the method and system for assessing the risk of traumatic blood loss proposed by the present invention have the following advantages: This paper proposes a method for assessing the risk of traumatic blood loss based on patient pupillary response data. By recording and analyzing changes in pupillary responses under different lighting conditions, baseline values ​​are determined and abnormal fluctuation intervals are identified, allowing prediction of the extent of blood loss and assessment of shock risk. This method not only rapidly acquires the data required for assessment, reducing diagnostic time, but also improves assessment accuracy, providing emergency physicians with more reliable decision-making support. Compared with traditional methods, this method can identify potential risks at an earlier stage, facilitate timely and effective treatment measures, and significantly improve patient outcomes. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of the method for assessing risk of traumatic blood loss of the present invention; Figure 2 FIG. 4 is a block diagram of a traumatic blood loss risk assessment system according to the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0018] The present invention provides Figure 1 The method shown here records and analyzes changes in a patient's pupillary response under different lighting conditions to determine baseline values ​​and identify abnormal fluctuation intervals, thereby predicting the extent of blood loss and assessing shock risk. This method not only rapidly acquires the data required for assessment, reducing diagnostic time, but also improves assessment accuracy, providing emergency physicians with a more reliable basis for decision-making. The method specifically includes the following steps: Step 1: Obtain the patient's pupil response data under different lighting conditions; the specific steps include: Record the initial pupil diameter D1 under initial ambient lighting conditions. Recording the patient's pupil diameter under natural light or standard ambient lighting conditions serves as the baseline for subsequent analysis. This initial value reflects the patient's normal pupil response characteristics and provides a benchmark for subsequent comparisons.

[0019] Adjust the ambient light intensity to a preset value and wait for the stabilization time T1; adjust the ambient light intensity to a fixed preset value (for example, darker light) and wait for a period of time to ensure that the pupil fully adapts to the new lighting conditions.

[0020] Measure the pupil diameter D2 after the stabilization time T1. After waiting for the stabilization time T1, measure the pupil diameter again to obtain the pupil's response under the new lighting conditions. This step provides a data point for comparison with the initial state, helping to identify the pupil's sensitivity to lighting changes.

[0021] Based on the pupil diameter at the initial time and after adjusting for ambient lighting, the pupil contraction rate R in response to lighting changes is calculated, where R = (D1-D2) / D1*100%. The significance of this formula is to quantify the pupil's sensitivity to lighting changes by comparing the pupil diameters under two different lighting conditions. A higher contraction rate indicates a more sensitive pupil to lighting changes, while a lower contraction rate indicates a slower pupil response. By calculating the rate of change in pupil diameter, the degree of pupil response to lighting changes can be quantified. This contraction rate can be used to further analyze the patient's physiological state, especially in cases of traumatic blood loss, where changes in pupil response may reflect the stress response of the nervous system.

[0022] Assume a patient needs to be assessed for risk of traumatic blood loss. Follow these steps: Record the initial pupil diameter D1 under the initial ambient lighting conditions: Under natural light conditions, the pupil diameter of the patient was measured using a pupillometer, and the result was D1 = 4.5 mm.

[0023] Adjust the ambient light intensity to the preset value and wait for the stabilization time T1: Adjust the ambient light intensity to a lower level (e.g., a dark room) and wait 3 minutes (T1 = 3 minutes) to ensure that the pupils have fully adapted to the new lighting conditions.

[0024] Measure the pupil diameter D2 after the stabilization time T1: In a dark room, after 3 minutes, the pupil diameter of the patient was measured again using a pupillometer, and the result was D2 = 6.0 mm.

[0025] Based on the pupil diameter at the initial time and after adjusting for ambient light, calculate the pupil contraction rate R in response to light changes: Use the formula R=(D1-D2) / D1*100% to calculate the contraction rate: R=(4.5-6.0) / 4.5*100%=-33.33%; In this example, the constriction rate is -33.33%, meaning the pupil dilates by 33.33% when the illumination changes from natural light to a darkened environment. This significant change may indicate that the patient's nervous system is in a highly sensitive state, providing an important reference for further assessment of the risk of traumatic blood loss.

[0026] Step 2: Determine the pupil response base state value based on the pupil response data; the specific steps include: The average pupil diameter M of N consecutive measurements is selected to provide a stable reference point. This average reflects the patient's general pupil diameter under specific lighting conditions and provides a benchmark for subsequent analysis.

[0027] The difference D_diff_i between each measurement and the mean M is calculated, where i is the number of measurements. By calculating the difference between each measurement and the mean, we can quantify the degree to which each measurement deviates from the mean. These differences can help identify fluctuations and anomalies in the data.

[0028] Calculate the sum of the squares of all the differences D_diff_i, S, where S = ∑(D_diff_i)^2. By squaring each difference and summing them, we can amplify large deviations and eliminate the effect of negative signs. This step helps assess the overall fluctuation of the data and provides a basis for further calculation of stability indicators.

[0029] Combining the mean value and the sum of squares, a basic state value BSV that can reflect the stability of pupillary response is calculated, where BSV=M-√(S / N). The closer the value is to the mean value M, the more stable the pupillary response; otherwise, it indicates a larger fluctuation.

[0030] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: Select the average value M of the pupil diameter in N consecutive measurements: Five measurements were performed, and the pupil diameters were: D1=4.5mm, D2=4.6mm, D3=4.7mm, D4=4.4mm, and D5=4.8mm.

[0031] Calculate the average value: M=(4.5+4.6+4.7+4.4+4.8) / 5=4.6mm.

[0032] Calculate the difference D_diff_i between each measurement value and the average value M: The difference is calculated as follows: D_diff_1=|4.5-4.6|=0.1mm; D_diff_2=|4.6-4.6|=0.0mm; D_diff_3=|4.7-4.6|=0.1mm; D_diff_4=|4.4-4.6|=0.2mm; D_diff_5=|4.8-4.6|=0.2mm; Find the sum S of the squares of all differences D_diff_i: The sum of squares is calculated as follows: S=(0.1^2+0.0^2+0.1^2+0.2^2+0.2^2)=0.09; Combining the mean and the sum of squares, a basic state value (BSV) that reflects the stability of pupillary response is calculated: Use the formula BSV=M-√(S / N): BSV=4.6-√(0.09 / 5)=4.6-√0.018≈4.6-0.134≈4.466mm.

[0033] Through the above steps and technical effects, this method can calculate a baseline state value (BSV) based on multiple pupil diameter measurements, reflecting the stability of pupillary response. This value not only takes into account the average level of pupil diameter but also the volatility of the data, thereby more comprehensively reflecting the patient's physiological status. In this example, the baseline state value (BSV) is approximately 4.466mm, indicating that the patient's pupillary response is relatively stable, providing an important reference for subsequent traumatic blood loss risk assessment.

[0034] Step 3: Adjusting the ambient light intensity according to the basic state value; the specific steps include: The target light intensity L0 is determined based on the baseline state value and the preset coefficient, where L0=BSV*k, where k is the preset coefficient; this step ensures that the adjustment of light intensity is based on the patient's pupil response characteristics, thereby enabling a more accurate assessment of their response to light changes.

[0035] Gradually increase or decrease the current ambient light intensity to the aforementioned L0, and record the pupil diameter PD_adj_j after each change, where j represents the number of adjustments. This step provides multiple data points to help observe the dynamic response of the pupil to light changes, providing a basis for further analysis.

[0036] The difference ΔPD_adj_j between the pupil diameter after each adjustment and the base state value BSV is calculated, where ΔPD_adj_j=|PD_adj_j-BSV|; these differences can help identify the sensitivity of the pupil to changes in lighting.

[0037] The average value AVG_ΔPD_adj of all differences ΔPD_adj_j is calculated, where AVG_ΔPD_adj=∑ΔPD_adj_j / N, where N is the number of adjustments. The AVG_ΔPD_adj is used as the evaluation standard for the final adjustment result. This indicator reflects the overall fluctuation of the pupil during the entire adjustment process.

[0038] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: Determine the target light intensity L0, where L0=BSV*k, k is the preset coefficient: The base state value BSV is 4.466 mm (obtained from the previous step), and the preset coefficient k is 0.8.

[0039] Target light intensity: L0=4.466*0.8=3.5728 (the unit depends on the specific situation, such as lux).

[0040] Gradually increase or decrease the current ambient light intensity to the above L0, and record the pupil diameter PD_adj_j after each change: Assume that we make three adjustments and the recorded pupil diameters are: PD_adj_1=4.3mm; PD_adj_2=4.5mm; PD_adj_3=4.4mm; The difference ΔPD_adj_j between the pupil diameter after each adjustment and the basic state value BSV is calculated: The difference is calculated as follows: ΔPD_adj_1=|4.3-4.466|=0.166mm; ΔPD_adj_2=|4.5-4.466|=0.034mm; ΔPD_adj_3=|4.4-4.466|=0.066mm; Find the average value AVG_ΔPD_adj of all differences ΔPD_adj_j: The mean difference is calculated as follows: AVG_ΔPD_adj=(0.166+0.034+0.066) / 3=0.0887mm.

[0041] Through the above steps and technical effects, this method can adjust the ambient light intensity based on the base state value BSV, record the pupil diameter after each adjustment, and calculate the impact of each adjustment on the pupil response. In this example, the target light intensity L0 is approximately 3.5728 lux. After three adjustments, the changes in pupil diameter are 0.166mm, 0.034mm, and 0.066mm, respectively, with an average difference AVG_ΔPD_adj of approximately 0.0887mm. This average difference indicates that the pupil's overall response to light changes is relatively stable throughout the adjustment process, providing an important reference for subsequent traumatic blood loss risk assessment.

[0042] Step 4: Monitor pupillary response changes after adjusting ambient light intensity. Specific steps include: First, make sure the ambient light has been adjusted to L0, and then wait for a stable period T_stable to ensure that the pupil fully adapts to the new lighting conditions.

[0043] The pupil diameter PD_L0 at the end of the stable period T_stable is recorded as the baseline value for subsequent measurements. This baseline value reflects the stable state of the pupil under the new lighting conditions.

[0044] Repeated pupil diameter measurements (PD_n) are performed at fixed intervals (ΔT), where n represents the number of measurements. By measuring pupil diameter multiple times within a fixed interval (ΔT), the dynamic response of the pupil to changes in illumination is captured. These data points help to visualize the trend of pupil diameter over time, providing a basis for further analysis.

[0045] Calculate the pupil diameter change rate (CR_n) for each measurement, where CR_n = (PD_n - PD_L0) / PD_L0 * 100%. Then, take the average of all these change rates, AVG_CR, where AVG_CR = ∑CR_n / M, where M is the number of measurements. By calculating and averaging the pupil diameter change rate for each measurement, we can quantify the pupil's overall response to light changes throughout the monitoring period. This average change rate reflects the overall fluctuation of pupillary response and provides a reliable reference for subsequent risk assessment.

[0046] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: First, make sure the ambient light has been adjusted to L0, and then wait for a stable period T_stable to ensure that the pupil fully adapts to the new lighting conditions: The ambient light has been adjusted to the target light intensity L0 (for example, 3.5728 lux), and the waiting period T_stable is 3 minutes.

[0047] Record the pupil diameter PD_L0 at the end of the stable period T_stable: After the stabilization period, the pupil diameter was measured using a pupillometer, and the result was PD_L0 = 4.4 mm.

[0048] Repeatedly measure pupil diameter PD_n at fixed time intervals ΔT: Assume that the pupil diameter is measured every 1 minute (ΔT = 1 minute), and a total of 5 measurements are performed, and the following data are obtained: PD_1=4.5mm; PD_2=4.6mm; PD_3=4.7mm; PD_4=4.6mm; PD_5=4.5mm; Calculate the pupil diameter change rate CR_n for each measurement and take the average value AVG_CR of all change rates: Calculate the rate of change for each measurement point: CR_1=(4.5-4.4) / 4.4*100%≈2.27%; CR_2=(4.6-4.4) / 4.4*100%≈4.55%; CR_3=(4.7-4.4) / 4.4*100%≈6.82%; CR_4=(4.6-4.4) / 4.4*100%≈4.55%; CR_5=(4.5-4.4) / 4.4*100%≈2.27%; Compute the average of all rates of change: AVG_CR=(2.27+4.55+6.82+4.55+2.27) / 5≈4.09%.

[0049] Through the above steps and technical effects, this method can, after adjusting the ambient light to the target light intensity L0, wait for a stabilization period to ensure that the pupil has fully adapted to the new lighting conditions. It then records the pupil diameter PD_L0 at the end of the stabilization period, measures the pupil diameter PD_n multiple times at a fixed time interval, and calculates the pupil diameter change rate CR_n for each measurement and its average value AVG_CR. In this example, over five measurements, the pupil diameter change rates were 2.27%, 4.55%, 6.82%, 4.55%, and 2.27%, respectively, for an average change rate of 4.09%. This average change rate reflects the pupil's overall response to light changes throughout the monitoring period and provides an important reference for subsequent traumatic blood loss risk assessment.

[0050] Step 5: Identify abnormal fluctuation intervals based on pupillary response changes; specific steps include: The fluctuation threshold WT is set by combining the average change rate AVG_CR and a preset coefficient t, where WT=AVG_CR*t, and t is the preset coefficient; this threshold is used to distinguish normal fluctuations from potential abnormal fluctuations, helping to identify time periods that require further analysis.

[0051] The pupil diameter change rate CR_n measured at each time is compared with the fluctuation threshold WT to identify the change rate that significantly deviates from the normal range.

[0052] Mark all time periods where CR_n is greater than WT as potential abnormal intervals PAI_j, where j represents the jth potential abnormal interval, so that we can focus on time periods that may have abnormal fluctuations.

[0053] Calculate the standard deviation SD_PA of pupil diameter change rate within each potential abnormal interval PAI_j, where , N is the number of measurements within the interval, and the PAI_j whose standard deviation exceeds the preset standard deviation threshold SDT is confirmed as the abnormal fluctuation interval AWI, so as to more accurately identify significant abnormal situations.

[0054] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: Set a fluctuation threshold WT, where WT=AVG_CR*t, t is the preset coefficient: Assume that the average change rate AVG_CR is 4.09% and the preset coefficient t is 1.5.

[0055] Fluctuation threshold: WT=4.09%*1.5≈6.135%; Compare the pupil diameter change rate CR_n measured at each time with the fluctuation threshold WT: The known rate of change of pupil diameter is: CR_1=2.27%; CR_2=4.55%; CR_3=6.82%; CR_4=4.55%; CR_5=2.27%; Mark all time periods where CR_n is greater than WT as potential abnormal intervals PAI_j: Compare each change rate with the fluctuation threshold WT (6.135%): CR_1 <WT; CR_2 <WT; CR_3>WT; CR_4 <WT; CR_5 <WT; Therefore, only CR_3 (6.82%) is greater than the fluctuation threshold WT and is marked as the potential abnormal interval PAI_1.

[0056] Calculate the standard deviation SD_PA of the pupil diameter change rate within each potential abnormal interval PAI_j, and identify the PAI_j whose standard deviation exceeds the preset standard deviation threshold SDT as an abnormal fluctuation interval AWI: In this example, there is only one potential abnormal interval PAI_1, which contains a change rate CR_3 = 6.82%.

[0057] Calculate the standard deviation SD_PA: ; Assume that the preset standard deviation threshold SDT is 2.5%.

[0058] Since SD_PA (2.73%) is greater than SDT (2.5%), PAI_1 is confirmed to be the abnormal fluctuation interval AWI.

[0059] Through the above steps and technical results, this method can identify abnormal fluctuation intervals based on pupillary response changes. In this example, after five measurements, only one time period (CR_3 = 6.82%) exceeded the fluctuation threshold WT (6.135%) and was marked as a potential abnormal interval PAI_1. Further calculation of its standard deviation SD_PA was 2.73%, exceeding the preset standard deviation threshold SDT (2.5%), thus confirming it as an abnormal fluctuation interval AWI. This method not only reduces diagnostic time but also improves assessment accuracy, helping emergency physicians make more reliable decisions.

[0060] Step 6: Compare the abnormal fluctuation range with the preset safety threshold; the specific steps include: The safety threshold ST is set by combining the average rate of change AVG_CR and a preset coefficient u, where ST=AVG_CR*u, where u is the preset coefficient; this threshold is used to distinguish normal fluctuations from high-risk fluctuations, helping to identify time periods that require special attention.

[0061] For each abnormal fluctuation interval AWI, the average value AVG_AWI of the pupil diameter change rate within the interval is calculated to quantify the overall fluctuation of these intervals.

[0062] The average value AVG_AWI of each abnormal fluctuation interval AWI is compared with the safety threshold ST to identify the change rate that significantly deviates from the normal range.

[0063] All abnormal fluctuation intervals where AVG_AWI exceeds ST are marked as high-risk intervals HRI_v, where v represents the vth high-risk interval, and the duration T_HRI of the HRI_v is recorded, so that attention can be focused on time periods with significant risks.

[0064] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: Set a safety threshold ST, where ST=AVG_CR*u, where u is the preset coefficient: Assume that the average change rate AVG_CR is 4.09% and the preset coefficient u is 1.2.

[0065] Safety threshold: ST = 4.09% * 1.2 ≈ 4.908%; For each abnormal fluctuation interval AWI, calculate the average value AVG_AWI of the pupil diameter change rate within the interval: In the previous step, we have identified an abnormal fluctuation range PAI_1 (i.e. AWI_1), which contains a change rate CR_3 = 6.82%.

[0066] Calculate the average rate of change over the interval: AVG_AWI_1=CR_3=6.82%; Compare the average value AVG_AWI of each abnormal fluctuation interval AWI with the safety threshold ST: Compare AVG_AWI_1 (6.82%) with the safety threshold ST (4.908%): AVG_AWI_1>ST; Mark all abnormal fluctuation intervals where AVG_AWI exceeds ST as high-risk intervals HRI_v, and record the duration T_HRI of the HRI_v: Since AVG_AWI_1 (6.82%) is greater than the safety threshold ST (4.908%), PAI_1 (i.e., AWI_1) is confirmed to be in the high-risk interval HRI_1.

[0067] Assume that the duration of the high-risk interval is 1 minute (T_HRI_1=1 minute).

[0068] Through the above steps and technical results, this method can compare abnormal fluctuation intervals with preset safety thresholds to identify high-risk intervals. In this example, after five measurements, only one time period (CR_3 = 6.82%) was identified as abnormal fluctuation interval AWI_1. Further calculation of its average rate of change was 6.82%, exceeding the safety threshold ST (4.908%), thus confirming it as high-risk interval HRI_1 and recording its duration as 1 minute. This method not only reduces diagnostic time but also improves assessment accuracy, helping emergency physicians make more reliable decisions.

[0069] Step 7: Use the comparison results to predict the extent of blood loss; the specific steps include: The blood loss coefficient (BLC) is set by calculating the sum of the durations of all high-risk intervals and combining it with the weight coefficient v of each high-risk interval, where BLC = ∑T_HRIv, where v is the weight coefficient of each high-risk interval HRI; this coefficient reflects the overall response of the patient's pupil to changes in light, especially those time periods that significantly deviate from the normal range.

[0070] The average pupil diameter change rate (AVG_HRI) for all high-risk intervals (HRI_v) was calculated (AVG_HRI = ∑AVG_AWI / V, where V is the total number of high-risk intervals) to quantify the overall fluctuation of these intervals. This step facilitates further analysis and identifies which intervals may be at higher risk, leading to a more accurate assessment of the extent of blood loss.

[0071] The blood loss degree coefficient BLC is combined with the average pupil diameter change rate AVG_HRI to generate a comprehensive evaluation value CEV, where CEV=BLCAVG_HRI; this value not only takes into account the duration of the high-risk interval, but also the fluctuation of pupil response, thereby more comprehensively reflecting the patient's blood loss degree.

[0072] The comprehensive evaluation value CEV is compared with the preset blood loss level threshold BLT to determine the patient's blood loss level. This step can quickly and accurately assess the patient's blood loss level and provide a reliable decision-making basis for emergency doctors.

[0073] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: Set a blood loss coefficient BLC, where BLC=∑T_HRIv, v is the weight coefficient of each high-risk interval HRI: Assume that there are two high-risk intervals HRI_1 and HRI_2, whose durations are T_HRI_1=1 minute and T_HRI_2=2 minutes respectively.

[0074] Assume that the weight coefficient v of each high-risk interval is 1.

[0075] Blood loss coefficient: BLC=T_HRI_1+T_HRI_2=1+2=3.

[0076] Calculate the average pupil diameter change rate AVG_HRI of all high-risk intervals HRI_v: The average change rate within the high-risk interval HRI_1 is AVG_AWI_1=6.82%.

[0077] The average change rate within the high-risk interval HRI_2 is AVG_AWI_2=5.70% (hypothetical value).

[0078] Calculate the average rate of change for all high-risk intervals: AVG_HRI=(AVG_AWI_1+AVG_AWI_2) / 2=(6.82%+5.70%) / 2≈6.26%; The blood loss coefficient BLC is combined with the average pupil diameter change rate AVG_HRI to generate a comprehensive evaluation value CEV: Comprehensive evaluation value: CEV=BLC*AVG_HRI=3*6.26%≈18.78%; The patient's blood loss level is determined by comparing the comprehensive evaluation value CEV with the preset blood loss level threshold BLT: Assume that the preset blood loss threshold BLT is: Mild blood loss: CEV < 10%; Moderate blood loss: 10% ≤ CEV < 20%; Severe blood loss: CEV ≥ 20%; In this case, the comprehensive evaluation value (CEV) was 18.78%, which was within the range of moderate blood loss.

[0079] Through the above steps and technical results, this method can predict a patient's blood loss severity using comparison results. In this example, after five measurements, two high-risk intervals, HRI_1 and HRI_2, were identified, with durations of 1 and 2 minutes, respectively. Further calculation of the blood loss severity coefficient (BLC) yielded a value of 3, and the average rate of change across all high-risk intervals was 6.26%, resulting in a composite assessment value (CEV) of 18.78%. Comparison with the preset blood loss threshold determined the patient's blood loss to be moderate.

[0080] Step 8: Assess the risk of shock based on the predicted degree of blood loss; specific steps include: The shock risk coefficient SRC is set by combining the comprehensive evaluation value CEV and a preset coefficient w, where SRC=CEV*w, w is the preset coefficient; this coefficient reflects the patient's potential shock risk based on the degree of blood loss and helps identify high-risk patients who require special attention.

[0081] Based on the patient's comprehensive assessment value CEV, the basic shock risk level (BLR) is determined, where BLR is the preset level corresponding to CEV; this step can quickly and accurately assess the patient's initial shock risk level and provide a basis for further risk modification.

[0082] The Shock Risk Modifier (SRM) is calculated as SRM = SRC + BLR. By combining the Shock Risk Factor (SRC) and the Basic Shock Risk Level (BLR), a modified SRM is generated. This SRM not only considers the impact of blood loss on shock risk but also incorporates the initial risk level, thereby more comprehensively reflecting the patient's shock risk.

[0083] The shock risk modification value (SRM) is compared with the preset shock risk threshold (SRT) to determine the patient's shock risk level. This step can quickly and accurately assess the patient's shock risk and provide a reliable decision-making basis for emergency doctors.

[0084] Suppose a patient requires a traumatic blood loss risk assessment. The steps are as follows: Set a shock risk coefficient SRC, where SRC=CEV*w, w is the preset coefficient: Assume that the comprehensive evaluation value CEV is 18.78% (obtained from the previous step) and the preset coefficient w is 0.5.

[0085] Shock risk coefficient: SRC=18.78%*0.5≈9.39%; The basic level of shock risk (BLR) is determined based on the patient's comprehensive assessment value (CEV): Assume that the preset shock risk level is: Mild shock risk: CEV < 10%; Moderate shock risk: 10% ≤ CEV < 20%; Risk of severe shock: CEV ≥ 20%; In this case, the comprehensive assessment value CEV is 18.78%, which is within the moderate shock risk range. Therefore, the basic level of shock risk BLR is moderate shock risk (assuming the value is 15).

[0086] Calculate the shock risk modification SRM, where SRM = SRC + BLR: Shock risk modification value: SRM=SRC+BLR=9.39+15≈24.39; The shock risk modification value SRM is compared with the preset shock risk threshold SRT to determine the patient's shock risk level: Assume that the preset shock risk threshold SRT is: Mild shock risk: SRM <10; Moderate shock risk: 10≤SRM<25; Risk of severe shock: SRM ≥ 25; In this case, the shock risk modification value (SRM) is 24.39, which is in the moderate shock risk range.

[0087] Through the above steps and technical results, this method can assess a patient's shock risk based on the predicted degree of blood loss. In this example, after five measurements, two high-risk intervals, HRI_1 and HRI_2, were identified, with durations of 1 and 2 minutes, respectively. The comprehensive evaluation value (CEV) was further calculated to be 18.78%, and the shock risk coefficient (SRC) was calculated using the formula SRC = CEV * w to be 9.39%. Based on the comprehensive evaluation value (CEV), the basic shock risk level (BLR) was determined to be moderate (15). The shock risk modification (SRM) was calculated to be 24.39 and compared with the preset shock risk threshold, ultimately determining the patient's shock risk level to be moderate.

[0088] This method not only reduces diagnostic time but also improves the accuracy of assessment, helping emergency physicians make more reliable decisions. This method can quickly and non-invasively obtain key data and improve the accuracy of assessment.

[0089] On the other hand, the present invention provides a traumatic blood loss risk assessment system, such as Figure 2 Shown, including: Pupil response data acquisition module, used to obtain patient pupil response data under different lighting conditions; a basic state value determination module, configured to determine a basic state value of pupil reaction based on the pupil reaction data; an ambient light adjustment module, configured to adjust the ambient light intensity according to the basic state value; Pupil response monitoring module, used to monitor pupil response changes after adjusting the ambient light intensity; An abnormal fluctuation interval recognition module is used to identify abnormal fluctuation intervals based on changes in pupil response; A safety threshold comparison module is used to compare the abnormal fluctuation range with a preset safety threshold; A blood loss degree prediction module, used to predict the blood loss degree using the comparison results; The shock risk assessment module is used to assess the risk of shock based on the predicted degree of blood loss.

[0090] In addition, when executed, each of the above modules is also used to implement other steps of the above traumatic blood loss risk assessment method, which will not be described in detail here.

[0091] In addition, the present invention also provides a terminal device. The traumatic blood loss risk assessment method involved in this embodiment is mainly applied to the terminal device, which can be a PC, portable computer, mobile terminal or other device with display and processing functions.

[0092] Specifically, a terminal device may include a processor (e.g., a CPU), a communication bus, a user interface, a network interface, and memory. The communication bus is used to enable communication between these components; the user interface may include a display and an input unit such as a keyboard; the network interface may optionally include a standard wired interface or a wireless interface (e.g., a Wi-Fi interface); and the memory may be high-speed RAM or non-volatile memory, such as disk storage. The memory may also be a storage device independent of the processor.

[0093] The memory stores a readable storage medium, and the readable storage medium stores a risk assessment program. The processor can call the risk assessment program stored in the memory and execute the traumatic blood loss risk assessment method provided by the embodiment of the present invention.

[0094] It will be understood that a computer-readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0095] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0096] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., utilizing an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions. The electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0097] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for assessing the risk of traumatic blood loss, characterized in that: The following steps are involved: Acquiring pupillary response data of the patient under different lighting conditions, and determining a basal state value of the pupillary response based on the pupillary response data; adjusting the ambient light intensity according to the basic state value, and monitoring changes in pupillary response after the ambient light intensity is adjusted; Identify abnormal fluctuation intervals based on changes in pupillary response, and compare the abnormal fluctuation intervals with a preset safety threshold; The comparison results were used to predict the extent of blood loss, and the risk of shock was assessed based on the predicted extent of blood loss.

2. A method for assessing risk of traumatic blood loss according to claim 1, characterized in that: The method of obtaining the patient's pupil response data under different lighting conditions includes: Record the initial pupil diameter D1 under the initial ambient lighting conditions; Adjust the ambient light intensity to the preset value and wait for a period of stabilization time T1; Measure the pupil diameter D2 after the stabilization time T1; Based on the pupil diameter at the initial time and after adjusting for ambient lighting, the pupil contraction rate R to the change in lighting is calculated, where R = (D1-D2) / D1*100%.

3. A method for assessing risk of traumatic blood loss according to claim 2, characterized in that: The determining of a basic state value of pupillary response based on the pupillary response data includes: Select the average value M of pupil diameter in N consecutive measurements; Calculate the difference D_diff_i between each measurement value and the average value M, where i is the number of measurements, and find the sum of the squares S of all the differences D_diff_i, where S=∑(D_diff_i)^2; Combining the mean and the sum of squares, a basic state value BSV that can reflect the stability of pupil response is calculated, where BSV=M-√(S / N).

4. A method for assessing risk of traumatic blood loss according to claim 3, characterized in that: The adjusting the ambient light intensity according to the basic state value includes: Determine the target light intensity L0 based on the basic state value and the preset coefficient, where L0=BSV*k, k is the preset coefficient; Gradually increase or decrease the current ambient light intensity to the target light intensity L0, and record the pupil diameter PD_adj_j after each change, where j represents the number of adjustments; Calculate the difference ΔPD_adj_j between the pupil diameter after each adjustment and the basic state value BSV, where ΔPD_adj_j=|PD_adj_j-BSV|, and obtain the average value AVG_ΔPD_adj of all differences ΔPD_adj_j, where AVG_ΔPD_adj=∑ΔPD_adj_j / N, N is the number of adjustments, and use the AVG_ΔPD_adj as the evaluation standard for the final adjustment result.

5. A method for assessing risk of traumatic blood loss according to claim 4, characterized in that: The monitoring of pupillary response changes after adjusting the ambient light intensity includes: First, ensure that the ambient light has been adjusted to the target light intensity L0, and wait for a stable period T_stable to ensure that the pupil fully adapts to the new lighting conditions; The pupil diameter PD_L0 at the end of the stable period T_stable was recorded, and the pupil diameter PD_n was repeatedly measured at fixed time intervals ΔT, where n represents the number of measurements; Calculate the pupil diameter change rate CR_n for each measurement, where CR_n=(PD_n-PD_L0) / PD_L0*100%, and calculate the average value AVG_CR of all change rates, where AVG_CR=∑CR_n / M, where M is the number of measurements.

6. A method for assessing risk of traumatic blood loss according to claim 5, characterized in that: The identifying of abnormal fluctuation intervals based on pupillary response changes includes: Setting a fluctuation threshold WT based on the average change rate AVG_CR and a preset coefficient t; Compare the pupil diameter change rate CR_n measured each time with the fluctuation threshold WT, and mark all time periods greater than the fluctuation threshold WT as potential abnormal intervals PAI_j, where j represents the jth potential abnormal interval; Calculate the standard deviation SD_PA of pupil diameter change rate within each potential abnormal interval PAI_j, where , N is the number of measurements within the interval, and the PAI_j whose standard deviation exceeds the preset standard deviation threshold SDT is confirmed as the abnormal fluctuation interval AWI.

7. A method for assessing risk of traumatic blood loss according to claim 6, characterized in that: Comparing the abnormal fluctuation range with a preset safety threshold includes: A safety threshold ST is set based on the average change rate AVG_CR and a preset coefficient u, where ST = AVG_CR * u, and u is the preset coefficient; For each abnormal fluctuation interval AWI, calculate the average value AVG_AWI of the pupil diameter change rate within the interval; Compare the average value AVG_AWI of each abnormal fluctuation interval AWI with the safety threshold ST; All abnormal fluctuation intervals where the average value AVG_AWI exceeds the safety threshold ST are marked as high-risk intervals HRI_v, where v represents the vth high-risk interval, and the duration T_HRI of the HRI_v is recorded.

8. A method for assessing risk of traumatic blood loss according to claim 7, characterized in that: The method of predicting the degree of blood loss by using the comparison results includes: The blood loss degree coefficient BLC is set based on the duration of the high-risk interval and the weight coefficient v, where BLC=∑T_HRIv, v is the weight coefficient of each high-risk interval HRI; Calculate the average pupil diameter change rate AVG_HRI of all high-risk intervals HRI_v, where AVG_HRI=∑AVG_AWI / V, V is the total number of high-risk intervals; Combining the blood loss degree coefficient BLC with the average pupil diameter change rate AVG_HRI to generate a comprehensive evaluation value CEV, where CEV=BLCAVG_HRI; The comprehensive evaluation value CEV is compared with a preset blood loss level threshold BLT to determine the patient's blood loss level.

9. The method for assessing risk of traumatic blood loss according to claim 8, wherein: The risk of shock is assessed based on the predicted degree of blood loss, including: The shock risk coefficient SRC is set based on the comprehensive evaluation value CEV and the preset coefficient w, where SRC = CEV*w, w is the preset coefficient. Based on the patient's comprehensive evaluation value CEV, the basic shock risk level BLR is determined, where BLR is the preset level corresponding to CEV; Calculate the shock risk modification value SRM, where SRM=SRC+BLR. The modified shock risk value SRM is generated by combining the shock risk coefficient SRC and the basic shock risk level BLR. The shock risk modification value SRM is compared with the preset shock risk threshold SRT to determine the patient's shock risk level.

10. A traumatic blood loss risk assessment system for implementing the method according to any one of claims 1 to 9, characterized in that: include: Pupil response data acquisition module, used to obtain patient pupil response data under different lighting conditions; a basic state value determination module, configured to determine a basic state value of pupil reaction based on the pupil reaction data; an ambient light adjustment module, configured to adjust the ambient light intensity according to the basic state value; Pupil response monitoring module, used to monitor pupil response changes after adjusting the ambient light intensity; An abnormal fluctuation interval recognition module is used to identify abnormal fluctuation intervals based on changes in pupil response; A safety threshold comparison module is used to compare the abnormal fluctuation range with a preset safety threshold; A blood loss degree prediction module, used to predict the blood loss degree using the comparison results; The shock risk assessment module is used to assess the risk of shock based on the predicted degree of blood loss.

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