Blood storage environment supervision method and system suitable for department of hematology

Abstract

The invention discloses a blood storage environment supervision method and system suitable for the department of hematology, relates to the field of biological sample storage environment supervision, and aims to solve the problems of irreversible damage to cells, reduction of blood bag quality and resource waste caused by unfreezing and washing. The method comprises the following steps: analyzing the similarity between a newly obtained red blood cell blood bag and a historical blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag, counting to obtain the ice crystal proportion of the historical blood bag, and obtaining the ice crystal forming probability of the newly obtained red blood cell blood bag based on Bayesian inference according to the proportion and the factor proportion thereof. Weighted average calculation is carried out according to newly-obtained red blood cell blood bag factors, the glycerin concentration of the newly-obtained red blood cell blood bag which needs to be unfrozen is obtained, interaction with an anticoagulant and a protection solution is analyzed, fuzzy logic is introduced to determine the optimal concentration result of the anticoagulant and the protection solution, the probability that ice crystals are formed by ice bags is estimated in advance, and unfreezing is carried out. And red blood cell damage and medical resource waste are reduced.

Description

Technical Field

[0001] The present invention relates to the field of biological sample storage environment supervision, and more specifically, to a blood storage environment supervision method and system suitable for hematology. Background Art

[0002] The effective storage of blood and its components is crucial to medical and blood transfusion services. It ensures that blood products are stored under appropriate temperature and environmental conditions to maintain their biological functions and effectiveness. Existing red blood cell storage technologies are divided into normal short-term storage and long-term storage to cope with the storage of red blood cell bags with different properties.

[0003] The prior art has the following deficiencies:

[0004] At present, when a hospital receives a batch of newly collected whole blood bags, it first uses centrifugation technology to divide red blood cells, plasma, platelets and other blood bags for classification and regional storage. Among them, glycerol is usually used as a cryoprotectant for frozen red blood cells. However, in the actual processing process, during the frozen storage of newly acquired red blood cell blood bags, the red blood cells and glycerol are not mixed evenly or the glycerol concentration is insufficient, which leads to ice crystal formation. The usual solutions include thawing, then adding glycerol and mixing again, or washing glycerol and adjusting to normal storage. Obviously, thawing and washing will cause irreversible damage to cells, reduce the quality of blood bags, and lead to waste of resources. Therefore, a blood storage environment supervision method and system suitable for hematology is proposed.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a blood storage environment monitoring method and system applicable to hematology, which solves the problems raised in the above-mentioned background technology by using different product inspection methods.

[0007] To achieve the above object, the present invention provides the following technical solution: a blood storage environment supervision method applicable to hematology, comprising S1: collecting historical blood bag information and newly acquired red blood cell blood bag information, obtaining historical blood bag glycerol concentration, historical blood bag freezing rate and historical environmental condition factors by querying historical red blood cell blood bag RFID tags, and performing similarity calculation with the corresponding information of the newly acquired red blood cell blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag;

[0008] S2: Obtain the similarity between historical blood bags and red blood cell blood bags, count the number of ice crystals in historical blood bags and the total number of historical blood bags to obtain the ice crystal ratio of historical blood bags, and obtain the probability of ice crystal formation in the newly acquired red blood cell blood bag based on the ratio and its factor ratios based on Bayesian inference;

[0009] S3: Obtain the probability of ice crystal formation of the newly acquired red blood cell blood bag, perform weighted average calculation based on the factors of the newly acquired red blood cell blood bag, and obtain the newly acquired red blood cell blood bag that most needs to be thawed;

[0010] S4: Obtain and analyze the newly obtained red blood cell blood bag that needs to be thawed the most, obtain its glycerol concentration, analyze the interaction between it and the anticoagulant and the protective solution, and obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution;

[0011] S5: Obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution, and bring them into fuzzy logic to determine the optimal concentration results of the anticoagulant and the protective solution.

[0012] In a preferred embodiment, after screening out historical blood bags that are consistent with the newly acquired red blood cell blood bag source information, blood bag material information, and blood bag volume information, the historical blood bag glycerol concentration, historical blood bag freezing rate, and historical environmental condition factors are collected;

[0013] The glycerol concentration of each historical blood bag is tracked through the label and recorded to obtain the historical blood bag glycerol concentration Gc i ; Where i is the i-th historical blood bag;

[0014] The freezing rate of each stage of each historical blood bag is tracked by tags, and the weighted average calculation is performed to obtain the historical blood bag freezing rate Va i ;

[0015] The environmental factors during the freezing period of the historical blood bags are detected by using temperature, humidity and air flow rate sensors set externally, and the historical environmental condition factors are obtained, including the average values ​​of the external temperature and humidity and the uniformity of the air flow in the storage box.

[0016] In a preferred embodiment, the similarity between the environmental condition factors of the newly acquired red blood cell blood bag information and the historical environmental condition factors is preferentially calculated based on the Euclidean distance through the average values ​​of the external temperature and humidity and the uniformity of the air flow in the storage box;

[0017] The similarity between the environmental condition factors, freezing rate and glycerol concentration was calculated by weighted average to obtain the similarity between the historical blood bag and the red blood cell blood bag.

[0018] In a preferred embodiment, the number of ice crystals formed in historical blood bags and the total number of historical blood bags are counted and a ratio is calculated to obtain the ice crystal ratio of historical blood bags;

[0019] Count the formation factors of each historical blood bag that formed ice crystals, and calculate the ratio between the factors and the total number of ice crystals formed, and take the maximum value as the main factor of ice crystal formation in the newly obtained red blood cell blood bag;

[0020] The probability of ice crystal formation in the newly acquired red blood cell blood bag is obtained based on Bayesian inference based on the ice crystal proportion of historical blood bags, the maximum factor proportion, and the similarity between historical blood bags and red blood cell blood bags.

[0021] In a preferred embodiment, the newly acquired red blood cell blood bag factors are divided into the utilization efficiency of red blood cells and the number of blood bags of corresponding types in the storage area;

[0022] The utilization efficiency of red blood cells is calculated by calculating the ratio of the number of blood bags having the same properties as the newly acquired red blood cell blood bags to the total number of blood bags used;

[0023] The difference in the consumption quantity of all blood bags in the storage area with the same properties as the newly acquired red blood cell blood bags within a fixed time;

[0024] The probability of ice crystal formation in a newly acquired red blood cell bag, the efficiency of red blood cell use, and the number of blood bags of this type in the storage area are weighted averaged, and the maximum value obtained is used as the newly acquired red blood cell bag that most needs to be thawed.

[0025] In a preferred embodiment, the glycerol concentration of the blood bag is obtained through a label on the surface of the blood bag;

[0026] By establishing the experimental analysis based on the linear regression model, the control experiment was conducted with different gradients of glycerol concentrations, anticoagulants and protective agents in the newly obtained red blood cell blood bags that needed to be thawed the most;

[0027] Specifically, the red blood cell survival rate and cell function index were set as dependent variables, the glycerol concentration was set as the independent variable, and the concentration of the anticoagulant and the protective solution were set as covariates; multiple groups of experiments were conducted to check the red blood cell survival rate and cell function index after mixing; among them, the viscosity and osmotic pressure of the mixed solution were measured to evaluate its effect on the cell survival rate;

[0028] Using the regression equation, the results of multiple groups of experiments are statistically expressed as follows:

[0029] Y=β0+β1·X1+β2·X2+β3·X3+∈

[0030] Where Y is the cell survival rate, β0 is the intercept, β1, β2, and β3 are the regression coefficients of the corresponding independent variables, X1, X2, and X3 are the glycerol concentration, anticoagulant concentration, and protective solution concentration, respectively, and ∈ is the error term;

[0031] The glycerol concentration of the newly obtained red blood cell blood bag that needs to be thawed the most is brought into the fitted model to obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution.

[0032] In a preferred embodiment, the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution are defined as input variables and divided into different fuzzy sets respectively;

[0033] The optimal concentration results of anticoagulant and protective solution are defined as output variables and divided into fuzzy sets;

[0034] Formulate fuzzy rules to describe the influence of glycerol concentration on anticoagulant and the influence of glycerol concentration on protective solution on the optimal concentration results of anticoagulant and protective solution;

[0035] Fuzzy reasoning is performed based on fuzzy rules to determine the concentration scheme of anticoagulant and protective solution.

[0036] A blood storage environment monitoring system suitable for hematology department includes a blood bag collection module, a crystallization probability module, a blood bag analysis module, and an action analysis module;

[0037] The blood bag collection module is used to collect historical blood bag information and newly acquired red blood cell blood bag information. By querying the historical red blood cell blood bag RFID tag, the historical blood bag glycerol concentration, historical blood bag freezing rate and historical environmental condition factors are obtained, and the similarity is calculated with the corresponding information of the newly acquired red blood cell blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag and send it to the crystallization probability module;

[0038] The crystallization probability module is used to obtain the similarity between historical blood bags and red blood cell blood bags, count the number of ice crystals in historical blood bags and the total number of historical blood bags to obtain the ice crystal ratio of historical blood bags, and based on the ratio and its factor ratio, obtain the probability of ice crystal formation in the newly acquired red blood cell blood bag based on Bayesian inference and send it to the blood bag analysis module;

[0039] The blood bag analysis module is used to obtain the probability of ice crystal formation of the newly obtained red blood cell blood bag, perform weighted average calculation based on the factors of the newly obtained red blood cell blood bag, obtain the newly obtained red blood cell blood bag that needs to be thawed the most, and send it to the action analysis module;

[0040] The effect analysis module is used to obtain and analyze the newly obtained red blood cell blood bags that need to be thawed the most, obtain their glycerol concentration, analyze their interactions with anticoagulants and protective solutions, obtain the influence coefficient of glycerol concentration on anticoagulants and the influence coefficient of glycerol concentration on protective solutions, and bring them into fuzzy logic to determine the optimal concentration results of anticoagulants and protective solutions.

[0041] Technical effects and advantages of the present invention:

[0042] 1. The present invention obtains the similarity between historical blood bags and red blood cell blood bags by analyzing the similarity between newly acquired red blood cell blood bags and historical blood bags, obtains the proportion of ice crystals in historical blood bags by statistics, obtains the probability of ice crystals forming in newly acquired red blood cell blood bags based on the proportion and its factor proportions, and obtains the probability of ice crystals forming in newly acquired red blood cell blood bags based on Bayesian inference. The weighted average calculation is performed based on the factors of the newly acquired red blood cell blood bags to obtain the newly acquired red blood cell blood bags that need to be thawed the most, and estimates the probability of ice crystals forming in ice bags in advance, thereby reducing the deep risks caused by thawing, reducing the damage to red blood cells and the waste of medical resources, and improving the utilization efficiency.

[0043] 2. The present invention obtains the glycerol concentration of the newly obtained red blood cell blood bag that needs to be thawed the most, analyzes the interaction with the anticoagulant and the protective solution, obtains the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution, and uses fuzzy logic to determine the optimal concentration results of the anticoagulant and the protective solution, optimizes the use of the anticoagulant and the protective solution, reduces the glycerol washing steps, reduces the risk of red blood cell damage, and improves the storage efficiency of the blood bag. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention is a flow chart of a method for supervising a blood storage environment applicable to hematology department.

[0045] Figure 2 The present invention is a module schematic diagram of a blood storage environment monitoring system suitable for hematology department. DETAILED DESCRIPTION

[0046] 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 described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] The present invention first describes the preconditions for cryopreservation of red blood cells. Specifically, cryopreservation is to fully mix glycerol as a cryoprotectant with red blood cells to increase the osmotic pressure inside and outside the cells to prevent ice crystals from forming and causing damage to red blood cells, and then reduce the temperature to below -80°C.

[0048] Specifically, there are usually three situations that lead to ice crystals in blood bags during frozen storage. The first is insufficient glycerol mixing during the processing process, the second is insufficient or excessive glycerol concentration, and the third is too fast or too slow freezing rate. Therefore, after first finding the proportion of ice crystals formed in historical blood bags similar to the newly acquired red blood cell blood bag, the factors that form ice crystals are queried, the probability of ice crystals forming in the newly acquired red blood cell blood bag is evaluated, and then multiple feature points are clustered based on the blood bag's own factors to find the newly acquired red blood cell blood bag that needs to be thawed the most;

[0049] Among them, the newly acquired red blood cell bags have been programmed to be frozen in a storage box according to the standard operating procedure (SOP). The implementation steps are as follows: ensure that the red blood cell bags are fully mixed with glycerol before freezing to ensure uniform distribution; secondly, set an appropriate freezing rate, usually using segmented freezing: quickly cool to a certain temperature in the initial stage, and then slow down the cooling rate to avoid ice crystal formation. The treated blood bags are then placed in a storage box pre-cooled to -80°C to ensure a fast and uniform freezing environment. Therefore, the newly acquired red blood cell bags do not have the phenomenon of ice crystal formation. This embodiment 1 predicts the newly acquired red blood cell bags that are most in need of thawing among the newly acquired red blood cell bags that do not currently have the phenomenon of ice crystal formation;

[0050] Example 1

[0051] See also Figure 1 , a blood storage environment supervision method applicable to hematology department, the specific operation process is as follows:

[0052] S1: Collect historical blood bag information and newly acquired red blood cell blood bag information, obtain historical blood bag glycerol concentration, historical blood bag freezing rate and historical environmental condition factors by querying historical red blood cell blood bag RFID tags, and perform similarity calculation with the corresponding information of the newly acquired red blood cell blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag;

[0053] Among them, the supervision system obtains the source information, blood bag material information and blood bag volume information of the newly acquired red blood cell blood bag based on the newly acquired red blood cell blood bag information (usually RFID tag information); by inputting the source information, blood bag material information and blood bag volume information of the red blood cell blood bag, the historical blood bags with the same information are screened out;

[0054] It should be noted that RFID tags are electronic tags that use radio waves for data transmission and identification. They are used to store and transmit information and read the information in the tag without contact. Therefore, RFID tags are often used in the field of blood bag storage to reduce contamination caused by human contact with blood bags.

[0055] Specifically, after screening out historical blood bags that are consistent with the newly acquired red blood cell blood bag source information, blood bag material information, and blood bag volume information, the system collects its historical blood bag glycerol concentration, historical blood bag freezing rate, and historical environmental condition factors;

[0056] It should be noted that the newly acquired red blood cell blood bag source information refers to the blood type, such as A, B, AB, and O blood types; the blood bag material information refers to the container material of the blood bag, such as PVC (polyvinyl chloride) material and polyolefin material, etc., and the blood bag volume information refers to the consistent volume of the blood bag;

[0057] The historical blood bag glycerol concentration refers to the specific concentration of glycerol used as a cryoprotectant during the cryopreservation of historical red blood cell blood bags. The acquisition logic is to track the glycerol concentration of each historical blood bag through the label and record it to obtain the historical blood bag glycerol concentration Gc i ; Where i is the i-th historical blood bag;

[0058] It should be noted that glycerol, as a cryoprotectant, increases the osmotic pressure inside and outside the cell, reduces water activity, and reduces the amount of water that can be crystallized, thereby effectively inhibiting the formation of ice crystals and reducing mechanical damage to the cell membrane, which can lead to red blood cell rupture.

[0059] The historical blood bag freezing rate refers to the freezing rate of historical red blood cell blood bags at each stage of the freezing process. The acquisition logic is to track the freezing rates of each stage of each historical blood bag through tags, and perform weighted average calculation to obtain the historical blood bag freezing rate;

[0060] Specifically, once the freezing rate changes during the freezing process of the historical blood bag, it will be recorded as a stage in the label. Therefore, there are multiple stages of freezing rates, and the specific formula is expressed as:

[0061]

[0062] In the formula, v g is the freezing rate of the g-th segment, ΔT is the temperature change of the segment, and Δt is the duration of the segment;

[0063] The freezing rates of all stages are calculated by weighted average, and the specific formula is:

[0064]

[0065] Where Va i is the historical blood bag freezing rate, ω g is the weight of each freezing rate;

[0066] It should be noted that the weight of each freezing rate can be set by the experimenter based on the time length and temperature range of the corresponding freezing stage, which will not be elaborated here;

[0067] The historical environmental condition factors refer to the external environmental conditions that affect the formation of ice crystals during the freezing and storage of historical red blood cell blood bags, specifically the external temperature and humidity and the uniformity of air flow in the storage box. The acquisition logic is to detect the environmental factors during the freezing period of the historical blood bags through the temperature, humidity and air flow rate sensors set outside to obtain the historical environmental condition factors, including the average values ​​of the external temperature and humidity and the uniformity of the air flow in the storage box;

[0068] Specifically, the average values ​​of the outside temperature and humidity during the freezing period can be calculated by integration:

[0069] and

[0070] Where, T out (t) represents the external temperature at time t, H out (t) represents the external humidity at time t, t0 and t1 are the start and end times of the freezing process, respectively;

[0071] It should be noted that the end time refers to the time when the blood bag is taken out. The factors for taking out include but are not limited to the formation of ice crystals, thawing, and the observation of insufficient red blood cells inside after thawing for disposal to meet medical needs;

[0072] The uniformity of air flow in the storage box is calculated by the air velocity sensor. The specific formula is as follows:

[0073]

[0074] In the formula, It represents the air velocity gradient at the position (x, y, z) inside the storage box at time t. The internal space of the storage box is V. The volume formula is obtained based on the length, width and height. dV represents the small volume element when integrating in the volume V.

[0075] It should be noted that when The closer it is to 0, the more uniform the air flow is and the more stable the freezing environment is.

[0076] Furthermore, the glycerol concentration, freezing rate and environmental condition factors of the newly acquired red blood cell blood bag information are obtained in a similar manner as described above and will not be described in detail here;

[0077] Priority is given to calculating the similarity between the environmental condition factors of the newly acquired red blood cell blood bag information and the historical environmental condition factors; the specific similarity formula is obtained based on the Euclidean distance:

[0078]

[0079] In the formula, and are the average values ​​of the external temperature and humidity of the newly obtained red blood cell blood bag, and are the average values ​​of the external temperature and humidity of the historical blood bags, and are the uniformity of air flow in the storage boxes of newly acquired red blood cell blood bags and historical blood bags, respectively, and S is the similarity of environmental condition factors;

[0080] Among them, the similarity of freezing rate and glycerol concentration is similar to the similarity calculation method mentioned above, which will not be described in detail here;

[0081] Specifically, similarity calculation methods include but are not limited to Euclidean distance and cosine similarity;

[0082] The similarity between the environmental condition factors, the freezing rate and the glycerol concentration is calculated by weighted average to obtain the similarity between the historical blood bag and the red blood cell blood bag;

[0083] S2: Obtain the similarity between historical blood bags and red blood cell blood bags, count the number of ice crystals in historical blood bags and the total number of historical blood bags to obtain the ice crystal ratio of historical blood bags, and obtain the probability of ice crystal formation in the newly acquired red blood cell blood bag based on the ratio and its factor ratios based on Bayesian inference;

[0084] The historical blood bag ice crystal ratio refers to the number of ice crystals formed in the above historical blood bags. Since the formation of ice crystals will directly lead to mechanical loss of cells, there is no need to consider its ratio factor or formation volume. Its acquisition logic is to count the number of ice crystals formed in historical blood bags and the total number of historical blood bags and calculate the ratio to obtain the historical blood bag ice crystal ratio;

[0085] The formation factors of each historical blood bag that formed ice crystals were counted, and the ratio of the factors to the total number of ice crystals was calculated. It can be understood by the experimenters that the factors that formed ice crystals include but are not limited to uneven glycerin mixing, insufficient glycerin concentration, too fast or too slow freezing rate, poor air flow in the storage box, etc. In this embodiment, uneven glycerin mixing, insufficient glycerin concentration, and too fast or too slow freezing rate are used as the main factors for statistics;

[0086] Among them, the uneven mixing of glycerin is due to the fact that the mixing operation after adding the corresponding glycerin is not mixed evenly. Specifically, the mixing time, stirring speed and other factors recorded are searched for to conduct sampling analysis to see if there is a concentration difference to determine whether the formation of ice crystals is caused by the uneven mixing of glycerin.

[0087] For insufficient glycerol concentration, find out the glycerol concentration added to the blood bag and its expected index to conduct concentration testing to determine whether ice crystal formation is caused by insufficient glycerol concentration;

[0088] If the freezing rate is too fast or too slow, check the water output during the gradient or segmented freezing of the blood bag or the difference between the surface temperature of the blood bag and the freezing temperature to determine whether ice crystal formation is caused by the freezing rate being too fast or too slow;

[0089] The proportion of each factor was obtained by statistics, and the maximum value was taken as the main factor for the formation of ice crystals in the newly obtained red blood cell blood bag;

[0090] The probability of ice crystals forming in the newly acquired red blood cell blood bag is obtained based on Bayesian inference based on the ice crystal proportion of the historical blood bag, the maximum factor proportion, and the similarity between the historical blood bag and the red blood cell blood bag; the specific contents are as follows:

[0091] Prioritize defining events, let A be the event of ice crystals forming in a newly acquired red blood cell bag, and let B be the historical data indicator (such as ice crystal ratio, maximum factor ratio, and similarity);

[0092] Through historical data, the prior probability P(A) is calculated, and the historical ice crystal ratio is calculated to obtain:

[0093] P(A) = historical ice crystal ratio

[0094] Calculate the likelihood probability. Under the given historical indicator B, calculate the probability of forming ice crystals P(B|A) by analyzing the distribution of blood bags that form ice crystals in historical data under the given indicator. For the case where ice crystals are not formed, calculate That is, the distribution of indicators when no ice crystals are formed;

[0095] The total evidence probability P(B) is calculated by the total probability formula:

[0096]

[0097] In the formula, The newly obtained red blood cell blood bag has no ice crystals formed;

[0098] According to Bayes' theorem, update the posterior probability P(A|B) of ice crystal formation:

[0099]

[0100] In the formula, the posterior probability of ice crystal formation P(A|B) is the probability of ice crystal formation in the newly obtained red blood cell blood bag;

[0101] It should be noted that Bayesian inference can effectively extract information from historical data and new evidence to help calculate the probability of ice crystals forming in new red blood cell bags;

[0102] Specifically, although there are a large number of newly acquired red blood cell bags, this embodiment mainly analyzes blood bags that are frozen and stored. Since the storage life of frozen blood bags is longer and the operation requires higher precision, it is necessary to analyze in advance the possibility of ice crystal formation in the newly acquired red blood cell bags in the future and take remedial measures in advance.

[0103] Furthermore, the experimenters limited the number of newly acquired red blood cell bags to be tested based on specific practical operations, which will not be elaborated here; for example, type O blood, because it does not contain A or B antigens, can be accepted by people of any blood type, and is therefore often used in emergency blood transfusions or large-scale blood transfusions. Although most type O blood is stored in a normal short-term storage method, a portion is still stored in a frozen state as a reserve blood source; therefore, this part of the blood bags requires more detailed supervision and optimized storage methods, etc.

[0104] It should be noted that normal short-term storage is to place the blood bag in an incubator or refrigerator at 2-6°C, add anticoagulants and protective fluid, and can be stored for up to 42 days;

[0105] S3: Obtain the probability of ice crystal formation of the newly acquired red blood cell blood bag, perform weighted average calculation based on the factors of the newly acquired red blood cell blood bag, and obtain the newly acquired red blood cell blood bag that most needs to be thawed;

[0106] It is understandable that the more likely a newly acquired red blood cell bag is to form ice crystals, the more likely it is that it must be thawed first. Instead, it is necessary to comprehensively consider the efficiency of red blood cell use and the number of blood bags of this type in the storage area. Therefore, when selecting thawing objects, multi-dimensional data analysis should be combined to ensure that the thawed blood bags can achieve the best clinical results.

[0107] The newly acquired red blood cell blood bag factors are divided into the efficiency of red blood cell use and the number of blood bags of this type in the storage area;

[0108] Among them, the utilization efficiency of red blood cells and the number of blood bags of this type in the storage area are obtained by the system through connecting to the hospital's online data. Specifically, the utilization efficiency of red blood cells is the frequency of use of blood bags with the same properties as the newly acquired red blood cell blood bags. Within a fixed time (optional, such as the period before the arrival of the newly acquired red blood cell blood bags and after frozen storage), the number of blood bags with the same properties as the newly acquired red blood cell blood bags is used and the total number of blood bags used is used to calculate the utilization efficiency of red blood cells;

[0109] The number of blood bags of this type in the storage area is the difference in the number of blood bags with the same properties as the newly acquired red blood cell blood bags in the storage area. The specific storage area includes blood bags in normal short-term storage and blood bags in frozen storage. The difference in the number of blood bags consumed in the storage area with the same properties as the newly acquired red blood cell blood bags within a fixed time.

[0110] It should be noted that the blood bag with the same properties as the newly acquired red blood cell blood bag refers to the blood bag with the same blood type and the same blood bag volume. By analyzing the utilization efficiency of the current blood bag and other factors, potential use possibilities can be found to avoid the formation of ice crystals under frozen storage and cause waste of resources;

[0111] The probability of ice crystal formation in the newly acquired red blood cell blood bag, the utilization efficiency of the red blood cells, and the number of blood bags of this type in the storage area are weighted averaged, and the maximum value obtained by the calculation is used as the newly acquired red blood cell blood bag that most needs to be thawed;

[0112] The present invention obtains the similarity between historical blood bags and red blood cell blood bags by analyzing the similarity between newly acquired red blood cell blood bags and historical blood bags, obtains the proportion of ice crystals in historical blood bags by statistics, and obtains the probability of ice crystals forming in newly acquired red blood cell blood bags based on the proportion and its factor proportions based on Bayesian inference, and then performs weighted average calculation based on the factors of the newly acquired red blood cell blood bags to obtain the newly acquired red blood cell blood bags that need to be thawed the most, estimates the probability of ice crystals forming in ice bags in advance, reduces the deep risks caused by thawing, reduces red blood cell damage and waste of medical resources, and improves utilization efficiency.

[0113] Example 2

[0114] In Example 1 of the present invention, an example is given to analyze the similarity between a newly acquired red blood cell bag and a historical blood bag to obtain the similarity between the historical blood bag and the red blood cell bag, and the percentage of ice crystals in the historical blood bag is obtained by statistics. Based on the percentage and the percentage of its factors, the probability of ice crystals forming in the newly acquired red blood cell bag is obtained based on Bayesian inference, and then weighted average calculation is performed with the factors of the newly acquired red blood cell bag to obtain the operation strategy of the newly acquired red blood cell bag that needs to be thawed the most. However, in Example 1, only how to find the newly acquired red blood cell bag that needs to be thawed the most is considered, and the thawing method has not been analyzed. In the prior art, the thawed blood bag is washed to remove the original glycerol part, and then an anticoagulant and a protective solution are added. However, this causes great damage to the inside of the cells, affects the quality of the blood bag, and cannot meet the characteristics of its continued short-term storage, resulting in a waste of resources. In view of the above problems, Example 2 of the present invention is further refined.

[0115] S4: Obtain and analyze the newly obtained red blood cell blood bag that needs to be thawed the most, obtain its glycerol concentration, analyze the interaction between it and the anticoagulant and the protective solution, and obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution;

[0116] Based on the prior art, the present invention analyzes the interaction between glycerol and the anticoagulant and protective solution added in normal short-term storage, balances the dilution effect of the anticoagulant and protective solution with glycerol, stabilizes the osmotic pressure that the cells can withstand, increases the storage life of some parts while avoiding the formation of ice crystals, improves resource utilization, and supervises blood bags to avoid resource waste caused by environmental factors or processing factors;

[0117] It should be noted that in normal short-term storage, anticoagulants are used to inhibit the coagulation mechanism and prolong the storage time of red blood cells, usually including citrate, heparin and glucose, etc. Protective agents are used to improve cell survival rate and protect cell structure, enhance cell resistance and reduce damage during freezing, usually including amino acids, glucose, inorganic salts and antioxidants, etc.

[0118] The logic for obtaining the glycerol concentration of the newly acquired red blood cell blood bag that needs to be thawed is to obtain the glycerol concentration of the blood bag through the label on the surface of the blood bag;

[0119] The influence coefficient of glycerol concentration on anticoagulant and the influence coefficient of glycerol concentration on protective solution are obtained by establishing experimental analysis based on linear regression model. Usually, different gradients of glycerol concentrations are set for the newly obtained red blood cell blood bags that need to be thawed the most to conduct control experiments with anticoagulants and protective agents;

[0120] It should be noted that the linear regression model is established in statistical software, usually R or SPSS statistical software. After running the linear regression analysis, the statistical software will provide R 2 Value; R 2 The value indicates the proportion of the dependent variable variation that the independent variable can explain, and its range is 0-1. The closer the value is to 1, the better the model fits. Specifically, in regression analysis, statistical software can list the p-value of each independent variable to test whether the independent variable has a significant effect on the dependent variable. Usually, a p-value less than 0.05 is considered statistically significant, indicating that at a 95% confidence level, the independent variable has a significant effect on the dependent variable.

[0121] Specifically, the red blood cell survival rate and cell function index were set as dependent variables, the glycerol concentration was set as the independent variable, and the concentration of the anticoagulant and the protective solution were set as covariates; multiple groups of experiments were conducted to check the red blood cell survival rate and cell function index after mixing; among them, the viscosity and osmotic pressure of the mixed solution were measured to evaluate its effect on the cell survival rate;

[0122] Using the regression equation, the results of multiple groups of experiments are statistically expressed as follows:

[0123] Y=β0+β1·X1+β2·X2+β3·X3+∈

[0124] Where Y is the cell survival rate, β0 is the intercept, β1, β2, and β3 are the regression coefficients of the corresponding independent variables, X1, X2, and X3 are the glycerol concentration, anticoagulant concentration, and protective solution concentration, respectively, and ∈ is the error term;

[0125] Analyze R separately 2 Values ​​and p-values ​​are used to evaluate the goodness of fit of the model and the significance of the independent variables;

[0126] The glycerol concentration of the newly obtained red blood cell blood bag that needs to be thawed is brought into the fitted model to obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution (i.e., β2 and β3). When other variables are controlled, the change in red blood cell survival rate is calculated for each unit increase in glycerol concentration.

[0127] S5: Obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution, and bring them into fuzzy logic to determine the optimal concentration results of the anticoagulant and the protective solution;

[0128] For example, "High", "Low", "Medium" for the effect coefficient of glycerol concentration on anticoagulant, "Many", "Less", "Average" for the effect coefficient of glycerol concentration on protective solution;

[0129] Formulate a set of fuzzy rules to describe the impact of different input variables on output variables. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0130] The influence coefficient of glycerol concentration on anticoagulant is marked as X, the influence coefficient of glycerol concentration on protective solution is marked as U, and the optimal concentration results of anticoagulant and protective solution are marked as C_results;

[0131] Then we can define:

[0132] Rule 1:IF(X is High)AND(U is Many)THEN(C_results is Low)

[0133] Rule 2:IF(U is Low)AND(U is Less)THEN(C_results is High) ...

[0135] Perform fuzzy reasoning based on fuzzy rules to determine the concentration scheme of anticoagulant and protective solution;

[0136] It should be noted that the division of fuzzy sets can be adjusted according to actual conditions. For example, although this embodiment takes three fuzzy sets as an example, it can actually be divided into more than three sets to facilitate better accurate adjustment according to different similarities.

[0137] Specifically, when the optimal concentration result of the anticoagulant and the protective solution is calibrated as "High", the concentration of the current blood bag is increased by 1.5% based on the application basis. Conversely, when the optimal concentration result of the anticoagulant and the protective solution is calibrated as "Low", the concentration of the current blood bag is decreased by 7.2% based on the application basis.

[0138] Furthermore, for the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution, the threshold value can be set according to the actual situation for judgment. For example, when the influence coefficient of glycerol concentration on the anticoagulant exceeds 59%, it is marked as "High", and when the influence coefficient of glycerol concentration on the protective solution is higher than 41%, it is marked as "Many", etc., which will not be elaborated here;

[0139] The concentration of the anticoagulant and protective solution will be adjusted according to the optimal concentration results of the anticoagulant and protective solution to balance the dilution effect of the anticoagulant and protective solution with glycerol and stabilize the osmotic pressure that the cells can withstand;

[0140] The present invention obtains the glycerol concentration of a newly obtained red blood cell blood bag that needs to be thawed the most, analyzes the interaction with the anticoagulant and the protective solution, obtains the influence coefficient of the glycerol concentration on the anticoagulant and the influence coefficient of the glycerol concentration on the protective solution, and introduces fuzzy logic to determine the optimal concentration results of the anticoagulant and the protective solution, optimizes the use of the anticoagulant and the protective solution, reduces the glycerol washing steps, reduces the risk of red blood cell damage, and improves the storage efficiency of the blood bag.

[0141] Example 3

[0142] See also Figure 2 , a blood storage environment monitoring system suitable for hematology department, including a blood bag collection module, a crystallization probability module, a blood bag analysis module, and an action analysis module;

[0143] The blood bag collection module is used to collect historical blood bag information and newly acquired red blood cell blood bag information. By querying the historical red blood cell blood bag RFID tag, the historical blood bag glycerol concentration, historical blood bag freezing rate and historical environmental condition factors are obtained, and the similarity is calculated with the corresponding information of the newly acquired red blood cell blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag and send it to the crystallization probability module;

[0144] The crystallization probability module is used to obtain the similarity between historical blood bags and red blood cell blood bags, count the number of ice crystals in historical blood bags and the total number of historical blood bags to obtain the ice crystal ratio of historical blood bags, and based on the ratio and its factor ratio, obtain the probability of ice crystal formation in the newly acquired red blood cell blood bag based on Bayesian inference and send it to the blood bag analysis module;

[0145] The blood bag analysis module is used to obtain the probability of ice crystal formation of the newly obtained red blood cell blood bag, perform weighted average calculation based on the factors of the newly obtained red blood cell blood bag, obtain the newly obtained red blood cell blood bag that needs to be thawed the most, and send it to the action analysis module;

[0146] The effect analysis module is used to obtain and analyze the newly obtained red blood cell blood bags that need to be thawed the most, obtain their glycerol concentration, analyze their interactions with anticoagulants and protective solutions, obtain the influence coefficient of glycerol concentration on anticoagulants and the influence coefficient of glycerol concentration on protective solutions, and bring them into fuzzy logic to determine the optimal concentration results of anticoagulants and protective solutions.

[0147] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0148] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0149] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0150] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0151] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0152] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0153] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0155] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0156] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A blood storage environment supervision method applicable to hematology department, characterized by: include: S1: Collect historical blood bag information and newly acquired red blood cell blood bag information, obtain historical blood bag glycerol concentration, historical blood bag freezing rate and historical environmental condition factors by querying historical red blood cell blood bag RFID tags, and perform similarity calculation with the corresponding information of the newly acquired red blood cell blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag; S2: Obtain the similarity between historical blood bags and red blood cell blood bags, count the number of ice crystals in historical blood bags and the total number of historical blood bags to obtain the ice crystal ratio of historical blood bags, and obtain the probability of ice crystal formation in the newly acquired red blood cell blood bag based on the ratio and its factor ratios based on Bayesian inference; S3: Obtain the probability of ice crystal formation of the newly acquired red blood cell blood bag, perform weighted average calculation based on the factors of the newly acquired red blood cell blood bag, and obtain the newly acquired red blood cell blood bag that most needs to be thawed; S4: Obtain and analyze the newly obtained red blood cell blood bag that needs to be thawed the most, obtain its glycerol concentration, analyze the interaction between it and the anticoagulant and the protective solution, and obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution; S5: Obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution, and bring them into fuzzy logic to determine the optimal concentration results of the anticoagulant and the protective solution.

2. A blood storage environment monitoring method applicable to hematology department according to claim 1, characterized in that: After screening out historical blood bags that are consistent with the newly acquired red blood cell blood bag source information, blood bag material information, and blood bag volume information, collect the historical blood bag glycerol concentration, historical blood bag freezing rate, and historical environmental condition factors; The glycerol concentration of each historical blood bag is tracked through the label and recorded to obtain the historical blood bag glycerol concentration Gc i ; Where i is the i-th historical blood bag; The freezing rate of each stage of each historical blood bag is tracked by tags, and the weighted average calculation is performed to obtain the historical blood bag freezing rate Va i ; The environmental factors during the freezing period of the historical blood bags are detected by using temperature, humidity and air flow rate sensors set externally, and the historical environmental condition factors are obtained, including the average values ​​of the external temperature and humidity and the uniformity of the air flow in the storage box.

3. A blood storage environment monitoring method applicable to hematology department according to claim 2, characterized in that: Based on the Euclidean distance, the similarity between the environmental condition factors of the newly acquired red blood cell blood bag information and the historical environmental condition factors is preferentially calculated through the average values ​​of the external temperature and humidity and the uniformity of the air flow in the storage box; The similarity between the environmental condition factors, freezing rate and glycerol concentration was calculated by weighted average to obtain the similarity between the historical blood bag and the red blood cell blood bag.

4. A blood storage environment monitoring method applicable to hematology department according to claim 3, characterized in that: The number of ice crystals formed in historical blood bags and the total number of historical blood bags are counted and the ratio is calculated to obtain the ice crystal ratio of historical blood bags; Count the formation factors of each historical blood bag that formed ice crystals, and calculate the ratio between the factors and the total number of ice crystals formed, and take the maximum value as the main factor of ice crystal formation in the newly obtained red blood cell blood bag; The probability of ice crystal formation in the newly acquired red blood cell blood bag is obtained based on Bayesian inference based on the ice crystal proportion of historical blood bags, the maximum factor proportion, and the similarity between historical blood bags and red blood cell blood bags.

5. A blood storage environment monitoring method applicable to hematology department according to claim 4, characterized in that: The factors of newly acquired red blood cell bags are divided into the efficiency of red blood cell use and the number of blood bags of the corresponding type in the storage area; The utilization efficiency of red blood cells is calculated by calculating the ratio of the number of blood bags having the same properties as the newly acquired red blood cell blood bags to the total number of blood bags used; The difference in the consumption quantity of all blood bags in the storage area with the same properties as the newly acquired red blood cell blood bags within a fixed time; The probability of ice crystal formation in a newly acquired red blood cell bag, the efficiency of red blood cell use, and the number of blood bags of this type in the storage area are weighted averaged, and the maximum value obtained is used as the newly acquired red blood cell bag that most needs to be thawed.

6. A blood storage environment monitoring method applicable to hematology department according to claim 1, characterized in that: Obtain the glycerol concentration of the blood bag through the label on the surface of the blood bag; By establishing the experimental analysis based on the linear regression model, the control experiment was conducted with different gradients of glycerol concentrations, anticoagulants and protective agents in the newly obtained red blood cell blood bags that needed to be thawed the most; Specifically, the red blood cell survival rate and cell function index were set as dependent variables, the glycerol concentration was set as the independent variable, and the concentration of the anticoagulant and the protective solution were set as covariates; multiple groups of experiments were conducted to check the red blood cell survival rate and cell function index after mixing; among them, the viscosity and osmotic pressure of the mixed solution were measured to evaluate its effect on the cell survival rate; Using the regression equation, the results of multiple groups of experiments are statistically expressed as follows: Y=β0+β1·X1+β2·X2+β3·X3+∈ Where Y is the cell survival rate, β0 is the intercept, β1, β2, and β3 are the regression coefficients of the corresponding independent variables, X1, X2, and X3 are the glycerol concentration, anticoagulant concentration, and protective solution concentration, respectively, and ∈ is the error term; The glycerol concentration of the newly obtained red blood cell blood bag that needs to be thawed the most is brought into the fitted model to obtain the influence coefficient of glycerol concentration on the anticoagulant and the influence coefficient of glycerol concentration on the protective solution.

7. A blood storage environment monitoring method applicable to hematology department according to claim 6, characterized in that: The influence coefficient of glycerol concentration on anticoagulant and the influence coefficient of glycerol concentration on protective solution are defined as input variables and divided into different fuzzy sets respectively. The optimal concentration results of anticoagulant and protective solution are defined as output variables and divided into fuzzy sets; Formulate fuzzy rules to describe the influence of glycerol concentration on anticoagulant and the influence of glycerol concentration on protective solution on the optimal concentration results of anticoagulant and protective solution; Fuzzy reasoning is performed based on fuzzy rules to determine the concentration scheme of anticoagulant and protective solution.

8. A blood storage environment monitoring system applicable to hematology department, used to implement a blood storage environment monitoring method applicable to hematology department as claimed in any one of claims 1 to 7, characterized in that: It includes blood bag collection module, crystallization probability module, blood bag analysis module and action analysis module; The blood bag collection module is used to collect historical blood bag information and newly acquired red blood cell blood bag information. By querying the historical red blood cell blood bag RFID tag, the historical blood bag glycerol concentration, historical blood bag freezing rate and historical environmental condition factors are obtained, and the similarity is calculated with the corresponding information of the newly acquired red blood cell blood bag to obtain the similarity between the historical blood bag and the red blood cell blood bag and send it to the crystallization probability module; The crystallization probability module is used to obtain the similarity between historical blood bags and red blood cell blood bags, count the number of ice crystals in historical blood bags and the total number of historical blood bags to obtain the ice crystal ratio of historical blood bags, and based on the ratio and its factor ratio, obtain the probability of ice crystal formation in the newly acquired red blood cell blood bag based on Bayesian inference and send it to the blood bag analysis module; The blood bag analysis module is used to obtain the probability of ice crystal formation of the newly obtained red blood cell blood bag, perform weighted average calculation based on the factors of the newly obtained red blood cell blood bag, obtain the newly obtained red blood cell blood bag that needs to be thawed the most, and send it to the action analysis module; The effect analysis module is used to obtain and analyze the newly obtained red blood cell blood bags that need to be thawed the most, obtain their glycerol concentration, analyze their interactions with anticoagulants and protective solutions, obtain the influence coefficient of glycerol concentration on anticoagulants and the influence coefficient of glycerol concentration on protective solutions, and bring them into fuzzy logic to determine the optimal concentration results of anticoagulants and protective solutions.

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