CVC catheter with center temperature monitoring function

Abstract

The invention discloses a CVC catheter with a central temperature monitoring function, and relates to the technical field of central temperature monitoring and analysis. The CVC catheter is used for monitoring the central vein temperature of a patient, and then the central vein temperature and all treatment-related indexes are combined to monitor the central vein temperature of the patient. The core targets of cooling precision and infusion individualization in the mild hypothermia treatment process are achieved, firstly, the temperature and the flow speed of cold saline water in a heat conduction pipe in the cooling stage of mild hypothermia treatment are obtained through analysis by combining the central vein temperature and all treatment related indexes; meanwhile, the optimal infusion speed is obtained through analysis in combination with the central vein temperature, all treatment related indexes and infusion medicine information, and finally in the sustaining stage of mild hypothermia treatment, the treatment stability condition of a patient is judged by monitoring the vein temperature. According to the application, the central vein temperature is taken as a data basis, a stable reference is provided for mild hypothermia treatment, and the safety, effectiveness and intelligence of mild hypothermia treatment are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of core temperature detection and analysis technology, specifically to a CVC catheter with core temperature monitoring function. Background Technology

[0002] Core temperature monitoring and analysis is the foundation of hypothermia therapy: on the one hand, it can accurately reflect the core body temperature status and ensure the stable achievement of treatment goals; on the other hand, by capturing temperature change trends and their correlation with other indicators, it provides a quantitative basis for assessing cooling efficiency, risk warning and parameter adjustment; therefore, this application proposes a CVC catheter with core temperature monitoring function.

[0003] Existing technology, such as the invention application patent with publication number CN219251216U, discloses a central venous catheter comprising a catheter body, a temperature measuring component, and an infusion tube. The catheter body has a temperature measuring channel and at least one infusion channel. The temperature measuring component includes a temperature probe and a wire connected to the temperature probe. The temperature probe is located within the temperature measuring channel and near the first end of the catheter body, and the wire extends out through the temperature measuring channel. The outer wall of the catheter body has an outlet side hole communicating with the infusion channel, and the distance between the outlet side hole and the first end of the catheter body is greater than the distance between the temperature probe and the first end of the catheter body. The number of infusion tubes is the same as the number of infusion channels. One end of the infusion tube is fixed to the second end of the catheter body and communicates one-to-one with the infusion channel, enabling fluid infusion while simultaneously and accurately monitoring body temperature in real time.

[0004] The above-mentioned solutions have the following technical problems: 1. The current technology only describes the structure of the catheter and does not take into account the practicality of central venous temperature monitoring through the CVC catheter. Traditional body temperature measurement is easily affected by the external environment and the patient's own emotional state, which will reduce the accuracy of body temperature measurement and thus affect the subsequent treatment plan and treatment effect.

[0005] 2. Current technology does not consider the correlation analysis between central venous temperature and hypothermia treatment. Due to the accuracy of central venous temperature, by comprehensively analyzing and monitoring various treatment parameters during hypothermia treatment based on central venous temperature and various treatment-related indicators, the treatment effect can be effectively guaranteed, avoiding the temperature error caused by traditional body temperature measurement to hypothermia treatment. Summary of the Invention

[0006] The purpose of this application is to provide a CVC catheter with a central temperature monitoring function, which solves the problems existing in the prior art.

[0007] To solve the above-mentioned technical problems, this application adopts the following technical solution: This application provides a CVC catheter with a central temperature monitoring function, including a CVC catheter body and a temperature monitoring and analysis system for the operation of the CVC catheter body. The temperature monitoring and analysis system includes: a hypothermia treatment analysis module: used to monitor the patient's central venous temperature through the CVC catheter when the patient is undergoing hypothermia treatment, and simultaneously obtain various treatment-related indicators of the patient, and then combine the patient's central venous temperature and various treatment-related indicators to analyze and obtain the temperature and flow rate of cold saline in the cooling tube during the hypothermia treatment cooling stage.

[0008] CVC catheter infusion analysis module: used to obtain drug information in CVC catheter during hypothermia treatment of patients. First, it determines whether to administer infusion to the patient. Then, based on the patient's central venous temperature, drug information in CVC catheter, temperature and flow rate of cold saline in cooling catheter, and various treatment-related indicators, it analyzes the optimal infusion rate for the patient.

[0009] Stability Analysis Module: Used for the maintenance phase of hypothermia therapy, it continuously monitors the patient's central venous temperature through a CVC catheter to analyze the patient's stability.

[0010] The beneficial effects of this application are as follows: 1. This application provides a CVC catheter with central venous temperature monitoring function. By using the CVC catheter, the patient's central venous temperature is monitored. Furthermore, by combining the central venous temperature with various treatment-related indicators, the core objectives of precise cooling and individualized infusion during hypothermia treatment are achieved. First, by combining the central venous temperature with various treatment-related indicators, the temperature and flow rate of the cold saline in the heat-conducting tube during the cooling phase of hypothermia treatment are analyzed. Simultaneously, by combining the central venous temperature, various treatment-related indicators, and infusion drug information, the optimal infusion rate is determined. Finally, during the maintenance phase of hypothermia treatment, the patient's treatment stability is assessed by monitoring the venous temperature. This application uses central venous temperature as a data foundation, providing a stable benchmark for hypothermia treatment and significantly improving the safety, effectiveness, and intelligence of hypothermia treatment.

[0011] 2. This application uses a CVC catheter to monitor the patient's central venous temperature instead of traditional body temperature measurement. During hypothermia treatment, peripheral temperature is easily affected by environmental factors, while the patient's body temperature is a key parameter in the hypothermia treatment process. Therefore, the central venous temperature monitored by the CVC catheter can directly reflect the core body temperature, thereby effectively ensuring the accuracy of temperature measurement and the stability of the treatment process.

[0012] 3. This application focuses on the precise control of the hypothermia cooling phase. By integrating central venous temperature with various treatment-related indicators, it dynamically outputs the temperature and flow rate of cold saline. By linking multiple indicators, it ensures the safety of treatment and transforms the treatment process from traditional experience-driven to accurate data-driven. This application also focuses on the precise control of infusion rate in hypothermia treatment. By integrating drug information, central venous temperature data, and various treatment-related indicators, it optimizes infusion decisions and outputs the optimal infusion rate based on multi-dimensional data. This achieves the core goals of precise cooling and individualized infusion in hypothermia treatment, improving the effectiveness and accuracy of hypothermia treatment. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of the system structure connection of this application. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] Reference Figure 1 As shown, this application provides a CVC catheter with a central temperature monitoring function, including a CVC catheter body and a temperature monitoring and analysis system for the operation of the CVC catheter body. The temperature monitoring and analysis system includes: a hypothermia treatment analysis module: used to monitor the patient's central venous temperature through the CVC catheter during hypothermia treatment, and simultaneously obtain various treatment-related indicators of the patient, and then combine the patient's central venous temperature and various treatment-related indicators to analyze and obtain the temperature and flow rate of cold saline in the cooling tube during the hypothermia treatment cooling phase.

[0017] In one specific instance, the acquisition of various treatment-related indicators for the patient includes the patient's core temperature difference, brain metabolic rate, and platelet count.

[0018] In a specific instance, the patient's treatment-related parameters were obtained as follows: the patient's peripheral temperature was measured using a thermometer, and the difference between the patient's central venous temperature and peripheral temperature was recorded as the patient's core temperature difference; the patient's platelet count was monitored using point-of-care testing (POCT).

[0019] Cerebral blood flow to the patient was measured using arterial spin labeling. Hemoglobin concentration, arterial oxygen saturation, and arterial oxygen partial pressure were measured using an arterial blood gas analyzer. The results were then calculated using the following formula: The patient's arterial oxygen content (CaO2), including Hb, SaO2, and PaO2, hemoglobin concentration, arterial oxygen saturation, and arterial oxygen partial pressure, were calculated. A blood sample was then obtained through a pre-embedded internal jugular vein catheter. Blood gas analysis of the blood sample yielded the patient's internal jugular vein oxygen saturation and partial pressure. Combining hemoglobin concentration, internal jugular vein oxygen saturation, and internal jugular vein oxygen partial pressure, the calculation formula was applied. The patient's internal jugular vein oxygen content (CjvO2) was calculated, where SjvO2 and PjvO2 represent the patient's internal jugular vein oxygen saturation and partial pressure of oxygen, respectively. Combining the patient's cerebral blood flow, arterial oxygen content, and internal jugular vein oxygen content, the calculation formula was used: The patient's brain metabolic rate CMRO2 was calculated.

[0020] It should be noted that the arterial spin labeling method, POCT method, and blood gas analysis are all existing testing techniques, and will not be described in detail here.

[0021] It should be noted that, for example, if a patient's Hb is measured to be 15 g / dL, SaO2 to be 98%, PaO2 to be 90 mmHg, SjvO2 to be 65%, PjvO2 to be 40 mmHg, and CBF to be 50 ml / 100 g / min, then the patient's arterial oxygen content is calculated to be 19.7 mLO2 / dL, and the internal jugular vein oxygen content is 13.1 mLO2 / dL. Therefore, the patient's brain metabolic rate is calculated to be 3.3 mLO2 / 100 g / min. The above examples are merely illustrative and not the only possible interpretations.

[0022] In a specific example, the method further combines the patient's central venous temperature and various treatment-related indicators to analyze and obtain the temperature and flow rate of the cold saline in the cooling tube during the hypothermia treatment cooling phase. The specific analysis process is as follows: obtain the average value of the patient's central venous temperature and the average value of the peripheral temperature within a preset time period, and calculate the patient's core temperature difference based on the average value of the patient's central venous temperature and the average value of the peripheral temperature.

[0023] The patient's core temperature difference, platelet count, brain metabolic rate, and basic information were standardized and then input into a pre-trained hypothermia treatment decision model. The optimal cooling effect achieved under stable treatment-related indicators was used as a constraint. The temperature and flow rate of the cold saline in the cooling tube during the patient's current hypothermia treatment were obtained through the hypothermia treatment decision model and model expression.

[0024] In a specific example, the decision-making model and model expression for hypothermia treatment are analyzed as follows: Using a hybrid logic model as the basic framework, the core temperature difference, platelet count, brain metabolic rate, and the patient's basic information are used as the inputs to the model. The temperature and flow rate of the cold saline in the cooling tube during hypothermia treatment are used as the outputs of the model. The various treatment-related indicators and the stability of the cooling process are used as the constraints of the model.

[0025] First, the core temperature difference, platelet count, and brain metabolic rate of each patient before and during hypothermia treatment in the hospital were standardized. Then, the temperature and flow rate of the cold saline in the cooling tube, as well as the basic information of each patient, were standardized. After standardization, the nonlinear relationship was quantified by a machine learning regression model. Then, the machine learning model with the quantified nonlinear relationship was integrated with a hybrid logic model. The hybrid logic model outputs the direction and amplitude of the cold saline in the cooling tube, and the machine learning model outputs the correction value of the direction and amplitude of the cold saline in the cooling tube. Based on this, the hypothermia treatment decision model and model expression are obtained.

[0026] Finally, the obtained hypothermia treatment decision model was embedded into the hospital's intensive care system.

[0027] It should be noted that, for example, the model expression of the hypothermia treatment decision model is: cold saline temperature = initial temperature + adjustment amount + correction amount; cold saline flow rate = baseline flow rate * correction coefficient. Furthermore, it is set that when the temperature difference between the target central venous temperature and the current central venous temperature is greater than 0.5 degrees Celsius, the initial temperature is the target central venous temperature minus 20 degrees Celsius; otherwise, the initial temperature is the target central venous temperature minus 10 degrees Celsius. The adjustment amount is set based on the patient's various treatment-related indicators. For example, if the patient's ΔCMRO2 is greater than 10%, the adjustment amount is -2 degrees Celsius; otherwise, it is 0 degrees Celsius. The correction amount is set based on the patient's basic information. For example, if the patient's age is greater than 65 years, the correction amount is +1 degrees Celsius; if the patient's weight is high... At 80 kg, the correction is -1℃, etc.; the baseline flow rate is the standard flow rate of cold saline obtained from the cooling tube equipment manual. The correction factor is set according to the temperature difference between the patient's target central venous temperature and the current venous temperature. For example, if ΔT > 2℃ and the patient's various treatment-related indicators are stable, the adjustment factor is 1.2, etc. When a patient's target central venous temperature is 33℃ and the current central venous temperature is 34.5℃, i.e., ΔT = 1.5℃, the target CMRO2 is 3.5 mLO2 / 100g / min, and the current CMRO2 is 1.7 mLO2 / 100g / min, i.e., ΔCMRO2 = 18%, and the core temperature difference is 2.5℃, PLT = 90 × 10⁻⁶. 9 If the patient is 70 years old and the standard flow rate of cold saline is found to be 15L / h, then the calculated temperature of the cold saline to the patient is 13℃ and the flow rate is 16L / h. The above example is only for illustrative purposes. The specific model and model expression need to be obtained based on historical data analysis and are not the only limitation.

[0028] CVC catheter infusion analysis module: used to obtain drug information in CVC catheter during hypothermia treatment of patients. First, it determines whether to administer infusion to the patient. Then, based on the patient's central venous temperature, drug information in CVC catheter, temperature and flow rate of cold saline in cooling catheter, and various treatment-related indicators, it analyzes the optimal infusion rate for the patient.

[0029] In a specific example, during the patient's hypothermia treatment, the drug information in the CVC catheter is obtained. First, it is determined whether to administer intravenous infusion to the patient. The specific analysis process is as follows: the drug name entered by the patient is obtained through the electronic medical record system, and then the drug name, suitable infusion temperature range and drug concentration are obtained from the drug instructions. The patient's central venous temperature is monitored during the hypothermia treatment.

[0030] The monitored central venous temperature is compared with the appropriate infusion temperature range of the drug. When the monitored central venous temperature is within the appropriate infusion temperature range of the drug, the optimal infusion rate of the drug is analyzed and the patient is given infusion. Conversely, when the monitored central venous temperature is not within the appropriate infusion temperature range of the drug, the patient's central venous temperature is continuously monitored until the temperature drops to the appropriate infusion temperature range of the drug. Then, the optimal infusion rate of the drug is analyzed and the patient is given infusion.

[0031] It should be noted that, for example, during hypothermia treatment, if the patient's current central venous temperature is 35°C and the appropriate infusion temperature range for the administered medication is 30-37°C, then the optimal infusion rate of the medication will be directly analyzed and the infusion will be administered to the patient. The above examples are merely illustrative and not the only possible interpretations.

[0032] In a specific example, the optimal infusion rate for the patient is analyzed based on the patient's central venous temperature, drug information and flow rate in the CVC catheter, and various treatment-related indicators. The specific process is as follows: During hypothermia treatment, the patient's central venous temperature is collected through the CVC catheter at each preset time point. The patient's central venous temperature at each preset time point, the drug information in the CVC catheter, and various treatment-related indicators are substituted into a pre-trained infusion rate decision model. The model is solved with the stability of each treatment-related indicator as a constraint to obtain the optimal infusion rate for the patient at each preset time point. The CVC catheter automatically adjusts according to the optimal infusion rate at each preset time point.

[0033] In a specific example, the infusion rate decision model is trained as follows: using a time-series regression model as the model framework, central venous temperature fluctuations and the stability of various treatment-related indicators are used as model constraints, drug information, various treatment-related indicators and central venous temperature are used as model inputs, and the optimal infusion rate is used as the model output, thus constructing an infusion rate decision model.

[0034] Infusion information of patients undergoing hypothermia treatment in hospitals throughout history was collected, standardized, time-series aligned, and subjected to interactive feature analysis and constraint determination. The data was then divided into training and validation sets according to a preset ratio. Bayesian optimization was used to optimize the parameters of the processed infusion information with the goal of maximizing the stability of the validation set indicators. Finally, a basic speed prediction module was constructed by combining a speed improvement decision tree model with a time-series regression model to obtain an infusion speed decision model and model expression.

[0035] It should be noted that the infusion information includes the central venous temperature, medication information, infusion rate, and related treatment indicators of each patient at each collection time point, all of which are recorded in the hospital's electronic medical record system.

[0036] It should be noted that the various data collection time points and preset ratios are all set by the relevant staff themselves, and no specific restrictions are imposed here; the standardization processing, time series alignment, interactive feature analysis, time series regression model and speed improvement decision tree model are all existing model technologies, and will not be described in detail here.

[0037] It should be noted that, for example, the model expression of the infusion rate decision model obtained through training is as follows: ,in To improve the base infusion rate output by the decision tree model, GBDT stands for Speed-Enhancing Decision Tree Model, where T is central venous temperature, D is drug type, and M is drug concentration. The rate of change of central venous temperature over 30 minutes. This is a constraint correction factor that is dynamically adjusted based on each treatment-related indicator, where i represents the number of each treatment-related indicator (i is a positive integer), and N is the total number of treatment-related indicators. This represents the deviation value of the treatment-related indicator numbered i. The weights corresponding to the deviation values ​​of the treatment-related indicators numbered i are: When a patient was taking pantoprazole at a concentration of 4 mg / ml, the central venous temperature was 34.5℃, the peripheral temperature was 34℃, the central venous temperature change rate over 30 minutes was 0.1℃ / h, the brain metabolic rate change was 28%, and the platelet count was 95*10. 9 At / l, the permissible fluctuation range for core temperature difference is 2℃, the fluctuation range for brain metabolic rate is less than 15% and greater than 35%, and the permissible range for platelet count is less than 80*10. 9 / l, the core temperature difference deviation of the patient can be calculated to be 0.5℃, while the brain metabolic rate and platelet count are within a reasonable range, therefore the calculation yields According to the output of the gradient boosting tree model Therefore, the optimal infusion rate was calculated to be 24 ml / h. The above is only an illustrative example and is not the only limitation.

[0038] Stability Analysis Module: Used for the maintenance phase of hypothermia therapy, it continuously monitors the patient's central venous temperature through a CVC catheter to analyze the patient's stability.

[0039] In a specific example, the patient's central venous temperature and various treatment-related indicators are continuously monitored through a CVC catheter to analyze the patient's stability. The specific analysis process is as follows: when the patient's central venous temperature drops to the target temperature for hypothermia treatment, the patient enters the hypothermia treatment maintenance phase. During the hypothermia treatment maintenance phase, the patient's central venous temperature is continuously monitored through a CVC catheter, and the central venous temperature is compared with the target temperature to determine whether the patient's current state is stable. When the patient's state is unstable, an alarm is triggered.

[0040] It should be noted that the target temperature is determined by relevant medical staff based on the patient's condition. For example, the target temperature for hypothermia treatment of patients with traumatic brain injury is 33-34℃.

[0041] It should be noted that the patient's real-time central venous temperature is compared with the target temperature to determine whether the patient's current condition is stable. For example, if the target temperature is 33-34℃ and the patient's central venous temperature at a certain moment is 33.5℃, it indicates that the patient's condition is stable.

[0042] In a specific example, the alarm prompts include voice alarm prompts and text alarm prompts. When a patient's central venous temperature is abnormal, a voice alarm is triggered via an alarm device connected to the nurses' station, and the alarm content includes the patient's ward number and bed number. At the same time, a text alarm is triggered via a monitoring display screen in the ward, and the alarm content includes the patient's abnormal central venous temperature and target temperature.

[0043] This application provides a CVC catheter with central venous temperature monitoring. By using the CVC catheter, the patient's central venous temperature is monitored. Furthermore, by combining central venous temperature with various treatment-related indicators, the core objectives of precise cooling and individualized infusion during hypothermia treatment are achieved. First, by combining central venous temperature with various treatment-related indicators, the temperature and flow rate of the cold saline in the heat-conducting tube during the cooling phase of hypothermia treatment are analyzed. Simultaneously, by combining central venous temperature, various treatment-related indicators, and infusion drug information, the optimal infusion rate is determined. Finally, during the maintenance phase of hypothermia treatment, the patient's treatment stability is assessed by monitoring venous temperature. This application uses central venous temperature as a data foundation, providing a stable benchmark for hypothermia treatment and significantly improving the safety, effectiveness, and intelligence of hypothermia treatment.

[0044] The above content is merely an example and illustration of the concept of this application. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the inventive concept or exceed the scope defined in this application, they should all fall within the protection scope of this application.

Claims

1. A CVC catheter with a central temperature monitoring function, comprising a CVC catheter body and a temperature monitoring and analysis system for the operation of the CVC catheter body, the temperature monitoring and analysis system comprising: Hypothermia Treatment Analysis Module: Used to monitor the patient's central venous temperature through a CVC catheter during hypothermia treatment, and simultaneously acquire various treatment-related indicators of the patient. Then, by combining the patient's central venous temperature and various treatment-related indicators, the module analyzes and obtains the temperature and flow rate of cold saline in the cooling tube during the hypothermia treatment cooling phase. CVC catheter infusion analysis module: used to obtain drug information in CVC catheter during hypothermia treatment of patients. First, it determines whether to administer infusion to the patient. Then, based on the patient's central venous temperature, drug information in CVC catheter, temperature and flow rate of cold saline in cooling catheter, and various treatment-related indicators, it analyzes the optimal infusion rate for the patient. Stability Analysis Module: Used for the maintenance phase of hypothermia therapy, it continuously monitors the patient's central venous temperature through a CVC catheter to analyze the patient's stability.

2. The CVC catheter with center temperature monitoring function according to claim 1, characterized in that, The acquisition of various treatment-related indicators for patients includes the patient's core temperature difference, brain metabolic rate, and platelet count.

3. A CVC catheter with center temperature monitoring function according to claim 2, characterized in that, The specific process for obtaining the patient's various treatment-related indicators is as follows: The patient's peripheral temperature was measured using a thermometer, and the difference between the patient's central venous temperature and peripheral temperature was recorded as the patient's core temperature difference; the patient's platelet count was monitored using point-of-care testing (POCT). Cerebral blood flow to the patient was measured using arterial spin labeling. Hemoglobin concentration, arterial oxygen saturation, and arterial oxygen partial pressure were measured using an arterial blood gas analyzer. The results were then calculated using the following formula: The patient's arterial oxygen content (CaO2), including Hb, SaO2, and PaO2, hemoglobin concentration, arterial oxygen saturation, and arterial oxygen partial pressure, were calculated. A blood sample was then obtained through a pre-embedded internal jugular vein catheter. Blood gas analysis of the blood sample yielded the patient's internal jugular vein oxygen saturation and partial pressure. Combining hemoglobin concentration, internal jugular vein oxygen saturation, and internal jugular vein oxygen partial pressure, the calculation formula was applied. The patient's internal jugular vein oxygen content (CjvO2) was calculated, where SjvO2 and PjvO2 represent the patient's internal jugular vein oxygen saturation and partial pressure of oxygen, respectively. Combining the patient's cerebral blood flow, arterial oxygen content, and internal jugular vein oxygen content, the calculation formula was used: The patient's brain metabolic rate CMRO2 was calculated.

4. A CVC catheter with center temperature monitoring function according to claim 3, characterized in that, Furthermore, by combining the patient's central venous temperature and various treatment-related indicators, the temperature and flow rate of the cold saline in the cooling tube during the hypothermia treatment cooling phase were analyzed. The specific analysis process is as follows: The average value of the patient's central venous temperature and the average value of the peripheral temperature within a preset time period are obtained, and the patient's core temperature difference is calculated based on the average value of the patient's central venous temperature and the average value of the peripheral temperature. The patient's core temperature difference, platelet count, brain metabolic rate, and basic information were standardized and then input into a pre-trained hypothermia treatment decision model. The optimal cooling effect achieved under stable treatment-related indicators was used as a constraint. The temperature and flow rate of the cold saline in the cooling tube during the patient's current hypothermia treatment were obtained through the hypothermia treatment decision model and model expression.

5. A CVC catheter with center temperature monitoring function according to claim 4, characterized in that, The specific analysis process of the hypothermia treatment decision model and model expression is as follows: Using a hybrid logic model as the basic framework, the core temperature difference, platelet count, brain metabolic rate, and basic patient information are used as inputs to the model. The temperature and flow rate of the cold saline in the cooling tube during hypothermia treatment are used as outputs to the model. Various treatment-related indicators and the stability of the cooling process are used as constraints to the model. First, the core temperature difference, platelet count, and brain metabolic rate of each patient before and during hypothermia treatment in the hospital were standardized. Then, the temperature and flow rate of the cold saline in the cooling tube, along with other basic patient information, were analyzed. A machine learning regression model was used to quantify the nonlinear relationships. This quantified machine learning model was then integrated with a hybrid logic model. The hybrid logic model outputs the direction and amplitude of the cold saline adjustment in the cooling tube, while the machine learning model outputs correction values ​​for these adjustments. Based on this, a hypothermia treatment decision model and its expression were obtained. Finally, the hypothermia treatment decision model was embedded into the hospital's intensive care system.

6. A CVC catheter with center temperature monitoring function according to claim 5, characterized in that, During the patient's hypothermia treatment, the drug information in the CVC catheter is obtained to first determine whether the patient needs intravenous infusion. The specific analysis process is as follows: The system obtains the name of the drug entered by the patient through the electronic medical record system, and then retrieves the drug name, appropriate infusion temperature range and drug concentration from the drug instructions. The patient's central venous temperature is monitored in real time during hypothermia treatment. The monitored central venous temperature is compared with the appropriate infusion temperature range of the drug. When the monitored central venous temperature is within the appropriate infusion temperature range of the drug, the optimal infusion rate of the drug is analyzed and the patient is given infusion. Conversely, when the monitored central venous temperature is not within the appropriate infusion temperature range of the drug, the patient's central venous temperature is continuously monitored until the temperature drops to the appropriate infusion temperature range of the drug. Then, the optimal infusion rate of the drug is analyzed and the patient is given infusion.

7. A CVC catheter with center temperature monitoring function according to claim 6, characterized in that, The optimal infusion rate for the patient is then analyzed based on the patient's central venous temperature, drug information and flow rate in the CVC catheter, and various treatment-related indicators. The specific process is as follows: During hypothermia treatment, the patient's central venous temperature is collected through a CVC catheter at each preset time point. The patient's central venous temperature at each preset time point, the drug information in the CVC catheter, and various treatment-related indicators are substituted into a pre-trained infusion rate decision model. The model is solved with the stability of each treatment-related indicator as a constraint to obtain the optimal infusion rate for the patient at each preset time point. The CVC catheter automatically adjusts according to the optimal infusion rate at each preset time point.

8. A CVC catheter with center temperature monitoring function according to claim 7, characterized in that, The specific training process for the infusion rate decision model is as follows: Using a time-series regression model as the model framework, central venous temperature fluctuations and the stability of various treatment-related indicators are used as model constraints. Drug information, various treatment-related indicators, and central venous temperature are used as model inputs, and the optimal infusion rate is used as model output to construct an infusion rate decision model. Infusion information of patients undergoing hypothermia treatment in hospitals throughout history was collected, standardized, time-series aligned, and subjected to interactive feature analysis and constraint determination. The data was then divided into training and validation sets according to a preset ratio. Bayesian optimization was used to optimize the parameters of the processed infusion information with the goal of maximizing the stability of the validation set indicators. Finally, a basic speed prediction module was constructed by combining a speed improvement decision tree model with a time-series regression model to obtain an infusion speed decision model and model expression.

9. A CVC catheter with center temperature monitoring function according to claim 8, characterized in that, The method involves continuous monitoring of the patient's central venous temperature and various treatment-related indicators via a CVC catheter to analyze the patient's stability. The specific analysis process is as follows: Once the patient's central venous temperature drops to the target temperature for hypothermia treatment, the hypothermia maintenance phase begins. During this phase, the patient's central venous temperature is continuously monitored via a CVC catheter and compared with the target temperature to determine if the patient's current condition is stable. An alarm is triggered if the patient's condition becomes unstable.

10. A CVC catheter with center temperature monitoring function according to claim 9, characterized in that, The alarm prompts include voice alarm prompts and text alarm prompts. When the patient's central venous temperature is abnormal, a voice alarm will be issued through an alarm device connected to the nurse station, and the alarm content will include the patient's ward number and bed number. At the same time, a text alarm will be issued through the monitoring display screen in the ward, and the alarm content will be the patient's abnormal central venous temperature and target temperature.

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