Perioperative period body temperature management method and system

Abstract

The invention discloses a perioperative period body temperature management method and system, and relates to the technical field of medical health data processing, and the system comprises a decision unit, a calculation unit, a communication unit, a body temperature acquisition unit, a manual input unit, a temperature control heating unit and the like. Based on multivariate data, a mathematical model which is efficient and high in response speed is established, intelligent decision-making adjustment of the body temperature is achieved, and the burden of medical staff in an operation is reduced; the risk of postoperative complications is reduced, the anesthesia effect and the recovery quality are improved, postoperative shivering and delayed waking are reduced, and the comfort and the satisfaction degree of a patient are improved; through effective body temperature and health information management, postoperative rehabilitation of a patient can be promoted, so that the hospitalization time is shortened, and medical resources are saved; and through an intelligent and individualized body temperature prediction and intervention technology, higher-quality perioperative period management is realized, and the development of precise medical treatment is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of medical and health data processing, and particularly relates to a perioperative body temperature management method and system. Background Art

[0002] Perioperative body temperature management is an important part of modern anesthesia and surgical care, aiming to maintain the core body temperature of patients within the normal range (generally 36.0°C to 37.5°C) during the preoperative, intraoperative, and postoperative stages to reduce the incidence of hypothermia-related complications. Research shows that the incidence of intraoperative unplanned hypothermia is as high as 20% - 70%, mainly due to factors such as the inhibition of the body temperature regulation center function caused by anesthesia, intraoperative exposure, infusion of cold fluids, and low environmental temperature.

[0003] Unplanned hypothermia refers to the phenomenon that the core body temperature of perioperative patients drops below 36.0°C, and its consequences are relatively serious, as follows: (1) Coagulation dysfunction and increased intraoperative blood loss: Hypothermia can inhibit platelet function and thrombin activity, prolong the coagulation time, increase intraoperative and postoperative blood loss, and pose a threat to surgical safety; (2) Increased postoperative infection rate: A decrease in body temperature will inhibit the activity of immune cells, reduce local tissue blood flow, delay wound healing, and significantly increase the risk of surgical site infection; (3) Increased risk of cardiovascular complications: Unplanned hypothermia can lead to vasoconstriction, blood pressure fluctuations, arrhythmias (such as atrial fibrillation), and increased myocardial oxygen consumption, especially having a greater impact on elderly patients or those with underlying cardiovascular diseases; (4) Delayed awakening and anesthetic metabolism disorders: Hypothermia can slow down the metabolic clearance rate of anesthetics, sedatives, and muscle relaxants by the liver and kidneys, delay the patient's waking time, and prolong the postoperative recovery period; (5) Shivering and increased discomfort: Postoperative shivering is a common reaction to hypothermia, which will increase oxygen consumption, myocardial burden, and the patient's subjective discomfort, and even lead to the risk of rebleeding; (6) Prolonged hospital stay and increased medical costs: The increase in complications and the extension of the recovery time will lead to an increase in the patient's postoperative hospital stay, further increasing the burden on hospital resources and economic costs.

[0004] In the prior art, there is a lack of a comprehensive decision-making body temperature management system for multi-data linkage at the surgical site, and it is impossible to achieve real-time collection and utilization of body temperature information and related health information. Summary of the Invention

[0005] The purpose of the present invention is to provide a perioperative body temperature management method and system based on real-time collection and linkage of multi-data, which calculates the body temperature through a body temperature prediction matrix operator and calculates the risk of hypothermia through a hypothermia risk probability model, and realizes automatic temperature control decision-making and postoperative data summary and filing.

[0006] For the above technical problems, the technical solution adopted by the present invention is: A perioperative body temperature management method, including the following steps: Step S1: Establish a uniquely corresponding online surgical information data table according to the patient's hospital admission number, and record the patient's name, surgical name, gender, age, height, weight, surgical site partition, anesthesia type, operating room environmental temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, intraoperative urine volume, and body temperature data. Among them, the patient's body temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, and intraoperative urine volume data are recorded every 5 - 10 minutes; Step S2: At the moment after the start of the surgery t , parameterize the parameters of the surgical information data table within the time interval ( t -1, t to obtain a parameter information data table. Export a body temperature prediction matrix operator according to the parameter information data table within the time interval ( t -1, t . Calculate the total predicted change in the patient's body temperature Δ t within the time interval ( t , t , t +1] based on the body temperature prediction matrix operator within the time interval ( T . Among them, t = 0, 1,..., n ; the unit of t is hours, and the unit of Δ T is °C; when t = 0, the time interval (-1,0] represents the time period from 1 hour before the start of the surgery to the start of the surgery; Step S3: Based on the patient's body temperature t at the moment T , the total predicted change in the patient's body temperature Δ t within the time interval ( t , T +1], and the normal distribution model, predict the low-temperature risk probability of the patient within the next hour. The condition for low temperature is that the body temperature is less than 35.5 °C; Step S4: Use a temperature control heating blanket to maintain or increase the patient's body temperature, and select a constant temperature control strategy or a variable temperature control strategy based on the calculation result of the low-temperature risk probability to control the real-time temperature of the temperature control heating blanket; Step S5: During the patient's recovery period in the anesthesia recovery room after the surgery, record the patient's body temperature data every 5 - 10 minutes. After the patient wakes up and enters the inpatient ward, summarize and file the body temperature data recorded during the surgery and the anesthesia recovery period as health management information, which is used as a reference for postoperative rehabilitation treatment to prevent postoperative complications caused by hypothermia during the perioperative period.

[0007] Furthermore, the body temperature prediction matrix operator includes a weight matrix W, and the expression of the weight matrix W is , wherein, is the first metabolic basic weight, and its value range is from 0.01 to 0.02; is the second metabolic basic weight, and its value range is from 0.001 to 0.002; is the hemodynamic weight, and its value range is from 0.001 to 0.003; is the net liquid cooling effect weight, and its value range is from -0.001 to -0.0006; is the time exposure weight, and its value range is from -0.08 to -0.07; is the environmental heat exchange weight, and its value range is from 0.04 to 0.07.

[0008] Furthermore, the body temperature prediction matrix operator further includes a coefficient matrix C, and the expression of the coefficient matrix C is , wherein, is the gender coefficient. When the patient is female, its value range is from 1.05 to 1.15; when the patient is male, its value range is from 0.95 to 1; is the age coefficient. When the patient's age is less than 30 years old, its value range is from 0.92 to 0.96; when the patient's age is between 30 and 65 years old, its value range is from 0.97 to 1.05; when the patient's age is greater than 65 years old, its value range is from 1.08 to 1.2; is the anesthesia coefficient. When the anesthesia type is general anesthesia, its value range is from 1.2 to 1.3; when the anesthesia type is intraspinal anesthesia, its value range is from 1.05 to 1.15; when the anesthesia type is local anesthesia, its value range is from 1 to 1.01; is the site coefficient. When the surgical site division belongs to the abdomen, its value range is from 1.27 to 1.35; when the surgical site division belongs to the chest, its value range is from 1.15 to 1.24; when the surgical site division belongs to the pelvis, its value range is from 1.02 to 1.06; when the surgical site division belongs to the lower limb or upper limb, its value is 1; when the surgical site division belongs to the head, its value range is from 0.95 to 0.99; is the urine volume correction coefficient. When the intraoperative urine volume is less than 200 ml, its value range is from 0.8 to 0.85; when the intraoperative urine volume is between 200 ml and 800 ml, its value range is from 0.95 to 1.05; when the intraoperative urine volume is greater than 800 ml but does not exceed 1500 ml, its value range is from 1.1 to 1.24; when the intraoperative urine volume is greater than 1500 ml, its value range is from 1.28 to 1.35.

[0009] Furthermore, the body temperature prediction matrix operator further includes a data element matrix D, and the expression of the data element matrix D is , Wherein, is the reference BMI index, and the value range is from 30 to 35; is the actual BMI index, which is calculated from the actual height and weight of the patient; is the age of the patient; is the reference age, and the value range is from 45 to 50; is the intraoperative blood loss; is the intraoperative blood transfusion volume; is the intraoperative infusion volume; is the net liquid cooling coefficient, and the value range is from 0.7 to 0.8; is the intraoperative urine volume; is the time exposure coefficient, and the value range is from -0.03 to -0.015; is the reference temperature, and the value range is from 20 to 22; is the operating room environmental temperature.

[0010] Furthermore, the calculation formula of Δ T is ; When t = 0, since the surgery has not started before this moment, the values of the surgery duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume and intraoperative urine volume are all 0; when t ≠ 0, the values of the intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume and intraoperative urine volume take the cumulative values in the time interval ( t -1, t .

[0011] Furthermore, assume that Δ T follows a normal distribution, that is , Then in the time interval ( t , t +1], the calculation formula for the predicted body temperature of the patient to be less than 35.5 °C is , wherein, the mean value The calculation formula is ; Wherein, is the reference mean value without considering the influence of the coefficient matrix C; is the anesthesia-site interaction mean value considering the interactive influence of the anesthesia type and the surgical site partition; is the age-fluid interaction mean value considering the interactive influence of the patient's age, intraoperative infusion volume and intraoperative urine volume; To consider the BMI-environment interaction mean under the interactive influence of the actual BMI index of the patient and the operating room environmental temperature; Is the anesthesia-site interaction coefficient, with a value range of 0.13 to 0.18; For calculating The intermediate variable during; Is the central parameter of the anesthesia type, with a value range of 1.4 to 1.6; Is the dispersion of the anesthesia effect, with a value range of 0.7 to 0.9; Is the central parameter of the surgical site, with a value range of 1.9 to 2.1; Is the dispersion of the site effect, with a value range of 1 to 1.4; Is the age-fluid interaction coefficient, with a value range of 0.002 to 0.005; Is the BMI-environment interaction coefficient, with a value range of -0.08 to -0.03; Variance The calculation formula of is ; In the formula, Is the anesthesia variance coefficient, with a value range of 0.06 to 0.09; Is the age variance coefficient, with a value range of 0.02 to 0.05.

[0012] Furthermore, when The value of does not exceed 50%, a constant temperature control strategy is adopted, and the temperature of the temperature control heating blanket is set to a constant temperature , The calculation formula of is ; In the formula, m Is the weight of the patient, in kg; H Is the specific heat capacity of the human body, in J / kg·°C; h Is the heat exchange coefficient, in W / m²·°C; A Is the contact area between the patient and the temperature control heating blanket, in m²; The meaning of the constant 3600 is 3600 seconds; When The value of is greater than 50%, a variable temperature control strategy is adopted, and the temperature of the temperature control heating blanket is set to a temperature that changes with time , The calculation formula of is ; In the formula, K Is the proportional adjustment factor, with a value range of 0.1 to 1; Is the target temperature, and the target temperature is the body temperature that the patient wants to reach and maintain; Is the real-time body temperature of the patient.

[0013] The present invention also provides a management system based on a perioperative body temperature management method, which includes a decision-making unit, a calculation unit, a communication unit, a body temperature acquisition unit, an artificial input unit, and a temperature control heating unit. The decision-making unit is used to send decision-making instructions externally, receive and process data, and store data; data interaction is carried out between the calculation unit and the decision-making unit; data interaction is carried out between the communication unit and the calculation unit; data interaction is carried out between the body temperature acquisition unit and the communication unit; data interaction is carried out between the temperature control heating unit and the decision-making unit; the artificial input unit is used to manually input the data collected by medical staff into the decision-making unit; the body temperature acquisition unit transmits the regularly collected body temperature data to the calculation unit through the communication unit, the decision-making unit transmits the data input by the artificial input unit to the calculation unit, the calculation unit calculates based on all the received data and transmits the result to the decision-making unit, the decision-making unit makes a temperature control decision-making plan according to the calculation result input by the calculation unit, and the decision-making unit controls the temperature of the temperature control heating unit in real time according to the temperature control decision-making plan; the temperature control heating unit uses a temperature control heating blanket.

[0014] Further, the communication unit includes a communication host, a display screen, a card reader, a communication interface, a power supply interface, a power button, function buttons, and indicator lights; the communication interface is arranged on the side of the communication host and is used for wired communication with the calculation unit; the power supply interface is arranged on the side of the communication host and is used for plugging in a power cord; the display screen is arranged on the upper surface of the communication host; one power button and multiple function buttons are all installed on the upper surface of the communication host; an indicator light is arranged beside each power button and function button; the card reader is fixedly installed on the communication host.

[0015] Further, the body temperature acquisition unit includes a main controller, an adhesive sticker, a signal wire, a sponge probe, a film, and a power button; the main controller is used to realize identification and pairing with the card reader by approaching or contacting; a circular adhesive sticker is fixedly installed on the side of the main controller; a film is attached to the adhesive sticker; the adhesive sticker is used for bonding with the patient's cheek skin after tearing off the film; the power button is arranged on the side of the main controller; the sponge probe is connected to the main controller through a signal wire.

[0016] The beneficial effects of the present invention compared with the prior art are as follows: (1) An efficient and fast-response mathematical model is established based on multiple data to realize intelligent decision-making regulation of body temperature, reducing the burden on medical staff during the operation; (2) The risk of postoperative complications is reduced, the anesthesia effect and recovery quality are improved, postoperative shivering and delayed awakening are reduced, and the comfort and satisfaction of patients are enhanced; (3) Through effective body temperature and health information management, the postoperative rehabilitation of patients can be promoted, thereby shortening the hospital stay and saving medical resources; (4) Through intelligent and individualized body temperature prediction and intervention technologies, higher-quality perioperative management can be achieved, which helps to promote the development of precision medicine. Description of the Drawings

[0017] Figure 1 This is the flowchart of the perioperative body temperature management method of the present invention.

[0018] Figure 2 This is the module diagram of the perioperative body temperature management system of the present invention.

[0019] Figure 3 This is the hardware structure diagram of the communication unit of the present invention.

[0020] Figure 4 This is the hardware structure diagram of the body temperature acquisition unit of the present invention.

[0021] In the figure: 1 - decision-making unit; 2 - calculation unit; 3 - communication unit; 4 - body temperature acquisition unit; 5 - manual input unit; 6 - temperature control heating unit; 301 - communication host; 302 - display screen; 303 - card reader; 304 - communication interface; 305 - power interface; 306 - power button; 307 - function button; 308 - indicator light; 401 - main controller; 402 - adhesive sticker; 403 - signal line; 404 - sponge probe; 405 - film coating; 406 - power-on key. Specific embodiments

[0022] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Among them, the accompanying drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as limiting the present invention; in order to better illustrate the embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0023] As Figure 1 shown, the perioperative body temperature management method proposed by the present invention includes the following steps: Step S1: Establish a uniquely corresponding online surgical information data table according to the patient's hospital admission number, and record the patient's name, surgical name, gender, age, height, weight, surgical site division, anesthesia type, operating room environmental temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, intraoperative urine volume and body temperature data. Among them, the patient's body temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume and intraoperative urine volume data are recorded every 10 minutes; as shown in Table 1, the partial core surgical information tables of 8 cases from Case 1 to Case 8 corresponding to Examples 1 to 8 are given.

[0024] Table 1 Partial core surgical information within 1 hour after the start of surgery for 8 groups of cases from Example 1 to Example 8

[0025] Step S2: At the moment after the start of the operationt , parameterize the surgical information data table within the time interval ( t -1, t to obtain the parameter information data table. Based on the parameter information data table within the time interval ( t -1, t , export the body temperature prediction matrix operator. Based on the body temperature prediction matrix operator within the time interval ( t -1, t , calculate the total predicted change in the patient's body temperature Δ t , t +1], where T , t =0, 1,..., n ; t is in hours, and Δ T is in °C; when t =0, the time interval (-1, 0] represents the period from 1 hour before the start of the surgery to the start of the surgery; in the 8 embodiments of the present invention, t are all equal to 1.

[0026] The body temperature prediction matrix operator includes a weight matrix W, a coefficient matrix C, and a data element matrix D. In the 8 embodiments of the present invention, the expression of the weight matrix W is , The expression of the coefficient matrix C is , The parameter value table of the coefficient matrix C corresponding to Embodiments 1 to 8 is shown in Table 2, where the anesthesia type in the 8 embodiments is general anesthesia; Table 2 Parameter values of the coefficient matrix C for a total of 8 groups of cases in Embodiments 1 to 8

[0027] The expression of the data element matrix D is , The parameter value table of the data element matrix D corresponding to Embodiments 1 to 8 is shown in Table 3; Table 3 Parameter values of the data element matrix D for a total of 8 groups of cases in Embodiments 1 to 8

[0028] Based on the above information, from the calculation formula of Δ T , the total predicted change in the patient's body temperature Δ T within the time interval (1, 2] can be obtained. The calculation results of Δ T are shown in Table 4.

[0029] Table 4 Calculation results of Δ for a total of 8 groups of cases from Example 1 to Example 8 T (unit: °C)

[0030] Step S3: Based on t the body temperature of the patient at the moment T , the total predicted change in the body temperature of the patient within the time interval ( t , t + 1], and the normal distribution model to predict the probability of low temperature risk for the patient within the next hour. The condition for low temperature is that the body temperature is less than 35.5 °C; let Δ T follow a normal distribution, that is T , t then within the time interval ( t , t + 1], the calculation formula for the predicted body temperature of the patient to be less than 35.5 °C is , where the mean is calculated by the formula ; In the formula, is the reference mean without considering the influence of the coefficient matrix C; is the anesthesia-site interaction mean considering the interactive influence of anesthesia type and surgical site partition; is the age-fluid interaction mean considering the interactive influence of the patient's age, intraoperative fluid infusion volume, and intraoperative urine volume; is the BMI-environment interaction mean considering the interactive influence of the patient's actual BMI index and operating room environmental temperature; in Examples 1 to 8, is the anesthesia-site interaction coefficient, and the values are all 0.15; is for calculating the intermediate variable; is the central parameter of the anesthesia type, and the values are all 1.5; is the anesthesia effect dispersion, and the values are all 0.8; is the central parameter of the surgical site, and the values are all 2.0; is the site effect dispersion, and the values are all 1.2; is the age-fluid interaction coefficient, and the values are all 0.004; is the BMI-environment interaction coefficient, and the values are all -0.05; the variance is calculated by the formula ; In Examples 1 to 8, is the anesthetic variance coefficient, and its value is 0.08 for all cases; is the age variance coefficient, and its value is 0.03 for all cases; Based on the above information, the calculation results of the 8 groups of cases from Example 1 to Example 8 are shown in Table 5; Table 5 Calculation results of the for the 8 groups of cases from Example 1 to Example 8

[0031] As can be seen from Table 5, only the value of Case 7 is greater than 50%.

[0032] Step S4: Use a temperature-controlled heating blanket to maintain or increase the patient's body temperature. Based on the calculation results of the low-temperature risk probability, select a constant-temperature control strategy or a variable-temperature control strategy to control the real-time temperature of the temperature-controlled heating blanket; when the value does not exceed 50%, adopt a constant-temperature control strategy, and the temperature of the temperature-controlled heating blanket is set to a constant temperature , The calculation formula of is In the formula, m is the patient's weight. The weight values of Cases 1 to 8 are shown in Table 1; H is the specific heat capacity of the human body, and its value is 3470 J / kg·°C in Examples 1 to 8; h is the heat exchange coefficient, and its value is 42 W / m²·°C in Examples 1 to 8; A is the contact area between the patient and the temperature-controlled heating blanket, and its value is 0.8 m² in Examples 1 to 8; The meaning of the constant 3600 is 3600 seconds; The body temperature and temperature data of the temperature-controlled heating blanket for a total of 6 groups of cases except Examples 2 and 7 are shown in Table 6. Recording starts 1 hour after the start of the operation and is recorded every 10 minutes until 2 hours after the start of the operation; Table 6 Body temperature (unit: °C) and temperature data of the temperature-controlled heating blanket for a total of 6 groups of cases except Examples 2 and 7

[0033] When the value is greater than 50%, that is, for Examples 2 and 7, adopt a variable-temperature control strategy, and the temperature of the temperature-controlled heating blanket is set to a temperature that changes with time , The calculation formula of is In the formula, K is the proportional adjustment factor, and its value is 0.6 in Examples 2 and 7; is the target temperature, which is 36°C in both Example 2 and Example 7. The target temperature is the body temperature that the patient is desired to reach and maintain. is the real-time body temperature of the patient. The body temperature and temperature control heating blanket temperature data of Example 2 are shown in Table 7, and the body temperature and temperature control heating blanket temperature data of Example 7 are shown in Table 8.

[0034] Table 7 Body Temperature and Temperature Control Heating Blanket Temperature Data of Example 2 (unit: °C)

[0035] Table 8 Body Temperature and Temperature Control Heating Blanket Temperature Data of Example 7 (unit: °C)

[0036] Step S5: During the patient's postoperative recovery period in the anesthesia recovery room, the patient's body temperature data is recorded every 10 minutes. After the patient wakes up and enters the inpatient ward, the body temperature data recorded during the operation and anesthesia recovery period is summarized and filed as health management information, which is used to provide a reference for postoperative rehabilitation treatment and prevent postoperative complications caused by hypothermia during the perioperative period.

[0037] The present invention also proposes a management system based on the aforementioned perioperative body temperature management method, as Figure 2 shown. The decision-making unit 1 is used to send decision-making instructions externally, receive and process data, and store data; data interaction is carried out between the calculation unit 2 and the decision-making unit 1; data interaction is carried out between the communication unit 3 and the calculation unit 2; data interaction is carried out between the body temperature acquisition unit 4 and the communication unit 3; data interaction is carried out between the temperature control heating unit 6 and the decision-making unit 1; the manual input unit 5 is used to manually input the data collected by medical staff into the decision-making unit 1; the body temperature acquisition unit 4 transmits the regularly collected body temperature data to the calculation unit 2 through the communication unit 3, the decision-making unit 1 transmits the data input by the manual input unit 5 to the calculation unit 2, the calculation unit 2 calculates based on all the received data and transmits the result to the decision-making unit 1, the decision-making unit 1 makes a temperature control decision-making plan according to the calculation result input by the calculation unit 2, and the decision-making unit 1 controls the temperature of the temperature control heating unit 6 in real time according to the temperature control decision-making plan; the temperature control heating unit 6 uses a temperature control heating blanket.

[0038] As Figure 3As shown in the figure, in the communication unit 3, the communication interface 304 is arranged on the side of the communication host 301 for wired communication with the computing unit 2; the power interface 305 is arranged on the side of the communication host 301 for plugging in the power cord; the display screen 302 is arranged on the upper surface of the communication host 301; a power button 306 and multiple function buttons 307 are both installed on the upper surface of the communication host 301; an indicator light 308 is arranged beside each of the power button 306 and the function buttons 307; the card reader 303 is fixedly installed on the communication host 301.

[0039] As Figure 4 shown in the figure, in the body temperature acquisition unit 4, the main controller 401 is used to realize identification and pairing with the card reader 303 by approaching or contacting; a circular adhesive sticker 402 is fixedly installed on the side of the main controller 401; a film 405 is attached to the adhesive sticker 402; the adhesive sticker 402 is used to bond with the patient's cheek skin after tearing off the film 405; the power-on key 406 is arranged on the side of the main controller 401; the sponge probe 404 is connected to the main controller 401 through a signal line 403.

[0040] The working principle of the present invention: In this embodiment, a computer integrated with the computing unit 2 and the decision-making unit 1 inside is adopted; as Figure 3 shown in the figure, before the patient enters the operating room, turn on the computer, connect the communication interface 304 and the computer through a data cable, connect the power interface 305 to the power supply, then long-press the power button 306 to turn on the communication host 301, and then set the data acquisition mode and activate the card reader 303 by pressing the function button 307; as Figure 4 shown in the figure, after the patient enters the operating room, turn on the power-on key 406 on the main controller 401, hold the main controller 401 and touch the card reader 303 to complete the wireless connection between the main controller 401 and the communication host 301; then, the sponge probe 404 is made of shape memory sponge material, and the medical staff rub the sponge probe 404 by hand to make the end of the sponge probe 404 thinner, insert the thinned sponge probe 404 into the patient's inner ear canal, keep it for 5 - 10 seconds, wait for the sponge probe 404 to recover its shape and fill the ear canal, then manually tear off the film 405, and bond the main controller 401 to the skin of the patient's cheek part through the adhesive sticker 402 to complete the deployment of the body temperature acquisition unit 4.

[0041] The body temperature acquisition unit 4 is a temperature-controlled heating blanket with heating and cooling functions, and the temperature-controlled heating blanket needs to be laid on the operating bed and connected to the computer before the patient starts the operation; the manual input unit 5 is a mouse and a keyboard connected to the computer. During the operation, there is a dedicated nurse responsible for manually recording the intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, and intraoperative urine volume data of the patient every 5 - 10 minutes, and inputting these data into the computer through the mouse and the keyboard; the computer realizes the automatic control of the temperature of the temperature-controlled heating blanket according to the aforementioned perioperative body temperature management method.

[0042] In particular, in the online surgical information data table established according to the patient's hospital admission number, the patient's name, surgical name, gender, age, height, weight, surgical site partition, and anesthesia type data are text data, and the operating room environmental temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, intraoperative urine volume, and body temperature data are numerical data; at the moment t after the start of the surgery, parameterizing the surgical information data table parameters in the time interval (t - 1, t] to obtain a parameter information data table means converting the text data other than the patient's name and the original numerical data in the surgical information data table into corresponding numerical data according to the calculation rule of Δ T of.

Claims

1. A perioperative body temperature management method, characterized in that, It includes the following steps: Step S1: Establish a uniquely corresponding online surgical information data table according to the patient's hospital admission number, and record the patient's name, surgical name, gender, age, height, weight, surgical site partition, anesthesia type, operating room environmental temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, intraoperative urine volume, and body temperature data. Among them, the patient's body temperature, surgical duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, and intraoperative urine volume data are recorded every 5 - 10 minutes; Step S2: At the moment after the operation starts t , parameterize the operation information data table within the time interval ( t -1, t to obtain the parameter information data table. Export the body temperature prediction matrix operator according to the parameter information data table within the time interval ( t -1, t . Calculate the total predicted change in the patient's body temperature Δ T within the time interval ( t , t + 1] according to the body temperature prediction matrix operator within the time interval ( t -1, t , where t = 0, 1, …, n ; t is in hours, and Δ T is in °C; when t = 0, the time interval (-1, 0] represents the time period from 1 hour before the operation starts to the start of the operation; Step S3: Based on t the patient's body temperature at a moment T , the total predicted change Δ t in the patient's body temperature within the time interval ( t , T + 1], and use the normal distribution model to predict the probability of the patient's low temperature risk within the next hour. The condition for low temperature is that the body temperature is less than 35.5°C; Step S4: Use a temperature control heating blanket to maintain or increase the patient's body temperature, and based on the calculation result of the low - temperature risk probability, select a constant - temperature temperature control strategy or a variable - temperature temperature control strategy to control the real - time temperature of the temperature control heating blanket; Step S5: During the patient's awakening period in the anesthesia recovery room after the operation, the patient's body temperature data is recorded every 5 - 10 minutes. After the patient wakes up and enters the inpatient ward, the body temperature data recorded during the operation and the anesthesia awakening period is summarized and filed as health management information, which is used to provide a reference for postoperative rehabilitation treatment and prevent postoperative complications caused by hypothermia during the perioperative period.

2. The perioperative body temperature management method according to claim 1, characterized in that: The body temperature prediction matrix operator includes a weight matrix W, and the expression of the weight matrix W is ， In the formula, is the first metabolic basic weight, and the value range is from 0.01 to 0.02; is the second metabolic basic weight, and the value range is from 0.001 to 0.002; is the hemodynamic weight, and the value range is from 0.001 to 0.003; is the net liquid cooling effect weight, and the value range is from -0.001 to -0.0006; is the time exposure weight, and the value range is from -0.08 to -0.07; is the environmental heat exchange weight, and the value range is from 0.04 to 0.

07.

3. The perioperative body temperature management method according to claim 2, characterized in that: The body temperature prediction matrix operator also includes a coefficient matrix C, and the expression of the coefficient matrix C is ， In the formula, is the gender coefficient, with a value range of 1.05 to 1.15 when the patient is female and a value range of 0.95 to 1 when the patient is male; is the age coefficient, with a value range of 0.92 to 0.96 when the patient's age is less than 30 years old, a value range of 0.97 to 1.05 when the patient's age is between 30 and 65 years old, and a value range of 1.08 to 1.2 when the patient's age is greater than 65 years old; is the anesthesia coefficient, with a value range of 1.2 to 1.3 when the anesthesia type is general anesthesia, a value range of 1.05 to 1.15 when the anesthesia type is intraspinal anesthesia, and a value range of 1 to 1.01 when the anesthesia type is local anesthesia; is the site coefficient, with a value range of 1.27 to 1.35 when the surgical site division belongs to the abdominal cavity, a value range of 1.15 to 1.24 when the surgical site division belongs to the thoracic cavity, a value range of 1.02 to 1.06 when the surgical site division belongs to the pelvic cavity, a value of 1 when the surgical site division belongs to the lower or upper extremities, and a value range of 0.95 to 0.99 when the surgical site division belongs to the head; is the urine volume correction coefficient, with a value range of 0.8 to 0.85 when the intraoperative urine volume is less than 200 ml, a value range of 0.95 to 1.05 when the intraoperative urine volume is between 200 ml and 800 ml, a value range of 1.1 to 1.24 when the intraoperative urine volume is greater than 800 ml but does not exceed 1500 ml, and a value range of 1.28 to 1.35 when the intraoperative urine volume is greater than 1500 ml.

4. The perioperative body temperature management method according to claim 3, characterized in that: The body temperature prediction matrix operator also includes a data element matrix D, and the expression of the data element matrix D is ， In the formula, is the reference BMI index, and its value range is from 30 to 35; is the actual BMI index, which is calculated from the actual height and weight of the patient; is the age of the patient; is the reference age, and its value range is from 45 to 50; is the intraoperative blood loss; is the intraoperative blood transfusion volume; is the intraoperative infusion volume; is the net liquid cooling coefficient, and its value range is from 0.7 to 0.8; is the intraoperative urine volume; is the time exposure coefficient, and its value range is from -0.03 to -0.015; is the reference temperature, and its value range is from 20 to 22; is the operating room environmental temperature.

5. The perioperative body temperature management method according to claim 4, wherein: Δ T The calculation formula is ； When t = 0, since the surgery has not started before this moment, the values of the surgery duration, intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, and intraoperative urine volume are all 0; when t ≠ 0, the values of the intraoperative blood loss, intraoperative blood transfusion volume, intraoperative infusion volume, and intraoperative urine volume are the cumulative values within the time interval ( t -1, t .

6. The perioperative body temperature management method according to claim 5, wherein: Let Δ T follow a normal distribution, that is ， Then in the time interval ( t , t + 1], the calculation formula for the patient's predicted body temperature less than 35.5 °C is ， Among them, the mean value The calculation formula is ； In the formula, is the baseline mean without considering the influence of the coefficient matrix C; is the anesthesia-site interaction mean considering the interactive influence of anesthesia type and surgical site partition; is the age-fluid interaction mean considering the interactive influence of the patient's age, intraoperative fluid infusion volume, and intraoperative urine volume; is the BMI-environment interaction mean considering the interactive influence of the patient's actual BMI index and the operating room environmental temperature; is the anesthesia-site interaction coefficient, and the value range is from 0.13 to 0.18; is for calculating when the intermediate variable; is the central parameter of anesthesia type, and the value range is from 1.4 to 1.6; is the anesthesia effect dispersion, and the value range is from 0.7 to 0.9; is the central parameter of the surgical site, and the value range is from 1.9 to 2.1; is the site effect dispersion, and the value range is from 1 to 1.4; is the age-fluid interaction coefficient, and the value range is from 0.002 to 0.005; is the BMI-environment interaction coefficient, and the value range is from -0.08 to -0.03; The variance The calculation formula of is ； In the formula, is the anesthesia variance coefficient, and its value range is from 0.06 to 0.09; is the age variance coefficient, and its value range is from 0.02 to 0.

05.

7. The perioperative body temperature management method according to claim 6, characterized in that: When does not exceed 50%, a constant temperature control strategy is adopted, and the temperature of the temperature control heating blanket is set to a constant temperature , The calculation formula of is ； Wherein, m is the weight of the patient, in kg; H is the specific heat capacity of the human body, in J / kg·°C; h is the heat exchange coefficient, in W / m²·°C; A is the contact area between the patient and the temperature-controlled heating blanket, in m²; the meaning of the constant 3600 is 3600 seconds; when is greater than 50%, a variable-temperature control strategy is adopted, and the temperature of the temperature-controlled heating blanket is set to a temperature that changes with time , The calculation formula of is ； Wherein, K is a proportional adjustment factor, and its value range is from 0.1 to 1; is the target temperature, which is the body temperature that the patient wants to reach and maintain; is the real-time body temperature of the patient.

8. A perioperative body temperature management system, which adopts a perioperative body temperature management method described in claim 7, includes a decision-making unit (1), a calculation unit (2), a communication unit (3), a body temperature acquisition unit (4), an artificial input unit (5), and a temperature control heating unit (6), and is characterized in that: The decision - making unit (1) is used to send decision instructions externally, receive and process data, and store data; the calculation unit (2) conducts data interaction with the decision - making unit (1); the communication unit (3) conducts data interaction with the calculation unit (2); the body temperature acquisition unit (4) conducts data interaction with the communication unit (3); the temperature control heating unit (6) conducts data interaction with the decision - making unit (1); the manual input unit (5) is used to manually input the data collected by medical staff into the decision - making unit (1); the body temperature acquisition unit (4) transmits the regularly collected body temperature data to the calculation unit (2) through the communication unit (3), the decision - making unit (1) transmits the data input by the manual input unit (5) to the calculation unit (2), the calculation unit (2) calculates based on all the received data and transmits the result to the decision - making unit (1), the decision - making unit (1) makes a temperature control decision plan according to the calculation result input by the calculation unit (2), and the decision - making unit (1) controls the temperature of the temperature control heating unit (6) in real - time according to the temperature control decision plan; the temperature control heating unit (6) uses a temperature control heating blanket.

9. The perioperative body temperature management system according to claim 8, characterized in that: The communication unit (3) includes a communication host (301), a display screen (302), a card reader (303), a communication interface (304), a power interface (305), a power button (306), function buttons (307), and indicator lights (308); the communication interface (304) is arranged on the side of the communication host (301) and is used for wired communication with the computing unit (2); the power interface (305) is arranged on the side of the communication host (301) and is used for plugging in a power cord; the display screen (302) is arranged on the upper surface of the communication host (301); one power button (306) and multiple function buttons (307) are both installed on the upper surface of the communication host (301); an indicator light (308) is arranged beside each power button (306) and function button (307); the card reader (303) is fixedly installed on the communication host (301).

10. The perioperative body temperature management system according to claim 9, characterized in that: The body temperature acquisition unit (4) includes a main controller (401), an adhesive sticker (402), a signal wire (403), a sponge probe (404), a film coating (405), and a power-on key (406); the main controller (401) is used to realize identification and pairing with the card reader (303) by approaching or contacting; a ring-shaped adhesive sticker (402) is fixedly installed on the side of the main controller (401); a film coating (405) is attached to the adhesive sticker (402); the adhesive sticker (402) is used for bonding with the patient's cheek skin after tearing off the film coating (405); the power-on key (406) is arranged on the side of the main controller (401); the sponge probe (404) is connected to the main controller (401) through the signal wire (403).

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