WO2023230957A1 - Ventilation analysis method, medical device, central station, and medical system - Google Patents

Abstract

A ventilation analysis method (100), a medical device (400), a central station (500), and a medical system (600). The ventilation analysis method (100) comprises: acquiring ventilation-related information on a ventilation object, the ventilation-related information at least comprising basic information, medical information, physiological data, and ventilation parameters of the ventilation object (S110); inputting the ventilation-related information into a ventilation analysis model to obtain a ventilation analysis result corresponding to the current ventilation mode, the ventilation analysis result at least comprising an evaluation result obtained by evaluating the current ventilation mode and influencing factors of the evaluation result (S120); and outputting the ventilation analysis result (S130). By means of the ventilation analysis model in combination with various ventilation-related information, the currently adopted ventilation mode is analyzed and evaluated, thereby giving objective and accurate suggestions and assisting a doctor in switching the ventilation mode in time when needed.

Description

Ventilation analysis methods, medical devices, central stations and medical systems

manual

Technical field

The present application relates to the field of medical equipment, and more specifically to a ventilation analysis method, medical equipment, central station and medical system.

Background technique

Respiratory failure is the most common organ dysfunction in critically ill patients and seriously threatens patients' lives. Especially in public health emergencies, respiratory failure becomes the main cause of death for patients. Respiratory support therapy is the most important treatment for patients with respiratory failure. A large proportion of patients in the ICU (Intensive Care Unit) require non-invasive or invasive mechanical ventilation treatment. Depending on the severity of the patient's respiratory failure and the response to treatment, clinically severe patients require different ventilation methods. How to accurately select ventilation methods for patients with respiratory failure is a major clinical challenge.

Currently, the choice of ventilation method for patients with respiratory failure is often based on the severity of respiratory failure and the clinician's judgment. Clinicians can make decisions based on the patient's physiological indicators, objective scoring tables, and subjective judgment. The bottleneck lies in the lack of unified standards for subjective judgment, and manual filling of forms results in low efficiency of doctors' diagnosis and treatment.

Contents of the invention

This summary introduces a series of concepts in a simplified form that are further described in detail in the detailed description. The invention summary part of this application is not intended to limit the key features and necessary technical features of the claimed technical solution, nor is it intended to determine the protection scope of the claimed technical solution.

The first aspect of the embodiments of the present application provides a ventilation analysis method, including:

Obtaining ventilation-related information of the ventilation subject, the ventilation-related information at least includes basic information, medical information, physiological data and ventilation parameters of the ventilation subject;

Input the ventilation-related information into the ventilation analysis model to obtain the ventilation analysis results corresponding to the current ventilation mode. The ventilation analysis results at least include the evaluation results obtained by evaluating the current ventilation mode and the influencing factors of the evaluation results;

Output the ventilation analysis results.

The second aspect of the embodiments of the present application provides a ventilation analysis method, which method is used in a central station and includes:

Obtain ventilation-related information of the ventilation object from the ventilation equipment and/or third-party equipment communicatively connected to the central station, where the ventilation-related information at least includes basic information, medical information, physiological data and ventilation parameters of the ventilation object;

Input the ventilation-related information into the ventilation analysis model to obtain ventilation analysis results corresponding to the current ventilation mode, where the ventilation analysis results at least include evaluation results of the current ventilation mode;

Send the ventilation analysis results to the ventilation equipment and/or third-party equipment.

A third aspect of the embodiment of the present application provides a medical device. The medical device includes a memory, a processor, and a display. The memory stores a computer program run by the processor. The computer program is processed by the processor. When the device is running, the steps of the ventilation analysis method as described above are performed to obtain ventilation analysis results, and the display is used to display the ventilation analysis results.

The fourth aspect of the embodiment of the present application provides a central station. The central station includes a memory, a processor and a communication unit. The memory stores a computer program run by the processor. The computer program is run by the processor. When the processor is running, the steps of the ventilation analysis method as described above are executed to obtain the ventilation analysis results, and the communication unit is used to send the ventilation analysis results obtained by the processor to the ventilation equipment that is communicatively connected to the central station.

A fifth aspect of the embodiment of the present application provides a medical system. The medical system includes a ventilation device and a central station as described above. The ventilation device is communicatively connected to the central station to receive and display information sent by the central station. The ventilation analysis results.

According to the ventilation analysis method, medical equipment, central station and medical system of the embodiment of the present application, the ventilation analysis model is combined with a variety of ventilation-related information to analyze and evaluate the currently adopted ventilation methods, and can give objective and accurate suggestions to assist doctors when necessary. Switch the ventilation mode promptly when necessary.

Description of the drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting any creative effort.

In the attached picture:

Figure 1 shows a schematic flow chart of a ventilation analysis method according to an embodiment of the present application;

Figure 2 shows a schematic flow chart of a ventilation analysis method according to another embodiment of the present application;

Figure 3 shows a schematic diagram of risk factors of assessment results according to an embodiment of the present application;

Figure 4 shows a schematic block diagram of a medical device according to an embodiment of the present application;

Figure 5 shows a schematic block diagram of a central station according to an embodiment of the present application;

Figure 6 shows a schematic block diagram of a medical system according to another embodiment of the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more apparent, exemplary embodiments according to the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the example embodiments described here. Based on the embodiments of the present application described in this application, all other embodiments obtained by those skilled in the art without creative efforts should fall within the protection scope of the present application.

In the following description, numerous specific details are given in order to provide a thorough understanding of the present application. However, it will be apparent to one skilled in the art that the present application may be practiced without one or more of these details. In other examples, some technical features that are well known in the art are not described in order to avoid confusion with the present application.

It will be understood that the application may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It will also be understood that the terms "consisting of" and/or "comprising", when used in this specification, identify the presence of stated features, integers, steps, operations, elements and/or parts but do not exclude one or more others The presence or addition of features, integers, steps, operations, elements, parts, and/or groups. When used herein, the term "and/or" includes any and all combinations of the associated listed items. In addition, the present application can be implemented in many different forms and is not limited to the embodiment described in this embodiment. The purpose of providing the following specific embodiments is to facilitate a clearer and thorough understanding of the disclosure content of the present application. The words indicating directions such as up, down, left, and right are only for the positions of the structures shown in the corresponding drawings.

In order to fully understand the present application, detailed structures will be provided in the following description to explain the technical solutions proposed in the present application. Optional embodiments of the present application are described in detail below, however, in addition to these detailed descriptions, the present application may also have other implementations.

Below, the ventilation analysis method according to the embodiment of the present application will be described with reference to the accompanying drawings. First, refer to FIG. 1 , which is a schematic flow chart of a ventilation analysis method 100 according to an embodiment of the present application. As shown in Figure 1, a ventilation analysis method 100 according to one embodiment of the present application includes the following steps:

In step S110, obtain ventilation-related information of the ventilation object, which at least includes the ventilation medical information, physiological data, and ventilation parameters; in some examples, the ventilation-related information may also include basic information of the ventilation object;

In step S120, the ventilation-related information is input into the ventilation analysis model to obtain the ventilation analysis results corresponding to the current ventilation mode. The ventilation analysis results at least include the evaluation results obtained by evaluating the current ventilation mode and the evaluation results. influencing factors;

In step S130, the ventilation analysis result is output.

The ventilation analysis method 100 in the embodiment of the present application can be implemented in ventilation equipment, such as ventilators, anesthesia machines, etc.; ventilation equipment is used to provide mechanical ventilation (such as invasive ventilation, non-invasive ventilation, oxygen therapy, etc.) for ventilation objects. The ventilation analysis results obtained based on the ventilation analysis method 100 can be output by the ventilation device, for example, can be displayed on a display of the ventilation device to serve as an objective reference for selecting a ventilation mode. In addition to ventilation equipment, the ventilation analysis method 100 of the embodiment of the present application can also be implemented in a central station, monitor, cloud service system or other electronic equipment.

Depending on the severity of respiratory failure and response to treatment of the ventilated subjects, the ventilation equipment uses different ventilation methods to provide mechanical ventilation to the ventilated subjects. Generally speaking, the ventilation methods that can be used for ventilation equipment are high-flow oxygen therapy, non-invasive ventilation or invasive ventilation. Among them, high-flow oxygen therapy is generally an oxygen therapy method that directly delivers a certain oxygen concentration of air oxygen mixed with high-flow gas to the ventilated object through a nasal tube or tracheal tube. It has the characteristics of high flow, precise oxygen concentration, and heating and humidification. , capable of correcting hypoxemia in ventilated subjects. Non-invasive ventilation methods refer to mechanical ventilation methods that do not require the establishment of artificial airways, including positive pressure ventilation in the airway and negative pressure ventilation outside the chest. Current non-invasive ventilation generally refers to non-invasive positive ventilation methods that are connected to the ventilation object through masks, nasal masks, etc. pressure mechanical ventilation. Invasive ventilation refers to a mechanical ventilation method that requires the establishment of an invasive artificial airway through endotracheal intubation or tracheotomy.

Among the above three ventilation methods, high-flow oxygen therapy improves hypoxia by increasing the flow of inhaled gas. Application of high-flow nasal oxygen therapy after extubation can improve oxygenation and reduce _CO2 retention. When high-flow oxygen therapy cannot maintain oxygenation or the oxygenation disorder tends to worsen, non-invasive mechanical ventilation or invasive mechanical ventilation can be switched. Compared with high-flow oxygen therapy, non-invasive ventilation reduces mortality, reduces patients' dyspnea scores and improves respiratory rate in patients with acute hypoxic respiratory failure. Given this, providing recommendations for switching from high-flow oxygen therapy to noninvasive or invasive ventilation has clinical value. On the other hand, high-flow oxygen therapy has clear advantages in terms of patient comfort and tolerability compared with non-invasive ventilation or invasive ventilation. Under non-invasive ventilation, if the condition of the ventilated subject does not improve or worsens, it is necessary to switch to invasive ventilation. On the contrary, under invasive ventilation, if the condition of the ventilated subject improves, it is necessary to switch to non-invasive ventilation or high-flow oxygen therapy ventilation to reduce complications related to invasive ventilation. It can be seen that the ventilation method should be switched in time according to the condition of the ventilation object to improve the treatment effect and ensure life safety.

Many factors need to be taken into consideration when switching ventilation methods. If the doctor decides which ventilation method to use, on the one hand, it is highly subjective and the accuracy of the judgment cannot be guaranteed; on the other hand, there are many factors that affect the ventilation method, and the efficiency of decision-making cannot be guaranteed. lower. The embodiment of this application uses a ventilation analysis model to analyze and evaluate the currently used ventilation methods, which can provide objective and accurate suggestions in real time, allowing doctors to switch ventilation methods in a timely manner when necessary.

Specifically, the ventilation analysis model combines multiple ventilation-related information to output ventilation analysis results, and the ventilation-related information is obtained in the process of providing mechanical ventilation to the ventilated object. Taking into account factors affecting ventilation mode, in some embodiments, ventilation-related information includes at least basic information, medical information, physiological data and ventilation parameters of the ventilation subject.

Among them, the basic information of the ventilation subject includes the age, gender, height, weight, etc. of the ventilation subject, which can affect the judgment of whether other parameters are normal or abnormal. For example, the younger the age, the faster the heart rate, and the heart rate of women is faster than that of men of the same age. Basic information about the ventilation object can be input by the user or automatically obtained by the device. For example, the data of the ventilation object can be obtained, keywords in the data can be extracted, and the basic information of the ventilation object can be obtained based on the extracted keywords. The ventilation object's information includes one or more of the ventilation object's patient information database, electronic medical records, examination application forms, etc. Alternatively, basic information about the ventilated object can be obtained through any other feasible method.

The medical information of the ventilated subject is also an important factor that affects the decision-making of ventilation mode, including but not limited to: the diagnosis result of the ventilated subject, past medical history, Acute Physiology and Chronic Health Evaluation (APACHE), sequential organ Failure (Sequential Organ Failure Assessment, SOFA) score, state of consciousness, vasoactive drug dosage, and sedation score. The medical information of the ventilated subject can be extracted from the Clinical Information System (CIS).

Among them, the diagnosis result of the ventilation object refers to the diagnosis result of the current diagnosis of the ventilation object, which directly affects the decision-making of the ventilation mode. Past medical history refers to historical diagnosis results, such as history of diabetes, cardiovascular and cerebrovascular diseases, various high-risk diseases, etc., which can be used as supplementary reference factors for ventilation methods.

The APACHEII score can indicate the severity of the condition. It is an evaluation result obtained by quantitatively evaluating the patient's condition based on objective physiological parameters. The higher the APACHEII score, the more serious the condition and the greater the need for invasive ventilation. high. The APACHEII score specifically includes acute physiology score, age score and chronic health score, and the final score is the sum of the three scores. The SOFA score can reflect the degree of dysfunction or failure of the respiratory system, blood system, liver system, cardiovascular system, nervous system and renal system. The higher the score, the worse the prognosis.

Vasoactive drugs include vasopressors, vasodilators, and inotropes. Vasoactive drugs can be used as auxiliary treatment during mechanical ventilation. For example, long-term mechanical ventilation can reflexively cause renal vasoconstriction, and vasodilator drugs can improve this problem. Therefore, evaluation of physiological data needs to consider the effects of vasoactive drugs. In addition to vasoactive medications, the ventilated subject's medical information may include other medication information.

The sedation score reflects the sedation status of the ventilated subject. Since ventilated subjects may become agitated during mechanical ventilation, leading to accidents such as human-machine confrontation and extubation, monitoring sedation scores can reduce accidents and promote synchronization of spontaneous breathing with the ventilator. For example, sedation scores include subjective scores such as Ramsay and SAD scores, and objective scores based on BIS, etc.

The medical information of the ventilated subject can reflect the long-term physiological state of the ventilated subject, while the physiological data of the ventilated subject reflects the current physiological state of the ventilated subject, which is more immediate. Exemplarily, the physiological data includes at least one of the following: physiological data collected by a ventilation device that provides ventilation for the ventilated subject reflecting the spontaneous breathing effort of the ventilated subject, physiological data reflecting the respiratory system status of the ventilated subject, and monitoring equipment associated with the ventilated subject. Collected vital sign parameters and inspection information of ventilation objects.

Among them, the physiological data reflecting the spontaneous breathing effort of the ventilated subject include but are not limited to the intensity and work of the ventilated subject's spontaneous breathing effort, and the physiological data reflecting the respiratory system status of the ventilated subject include but are not limited to lung compliance and airway resistance. Among them, lung compliance refers to the change in lung volume caused by a change in unit pressure, which represents the impact of changes in thoracic pressure on lung volume. Lung compliance can specifically include static lung compliance (Cst) and dynamic lung compliance ( Cdyn); airway resistance refers to the pressure difference generated by unit flow in the airway, which can better reflect the obstruction of the airway; spontaneous breathing effort intensity and work are used to evaluate whether the ventilated subject can tolerate spontaneous breathing. Among them, lung compliance and airway resistance are measured and used only during invasive ventilation.

Vital sign parameters directly reflect the physiological state of the ventilated subject, including at least one of the following: heart rate, respiratory rate, blood pressure, transcutaneous finger pulse oxygen saturation, and end-tidal carbon dioxide partial pressure. Among them, heart rate and blood pressure are the patient's basic vital sign parameters; respiratory rate is the number of breaths per minute; transcutaneous finger pulse oximeter is the blood oxygen saturation measured using the non-invasive pulse oximetry method; end-tidal carbon dioxide Pressure refers to the partial pressure of carbon dioxide contained in the mixed alveolar air exhaled at the end of expiration.

The test information of the ventilated subject includes at least one of blood routine results and blood gas results. Among them, blood routine results include red blood cell count, hemoglobin concentration, white blood cell concentration, white blood cell differential count, platelet concentration, etc. Blood routine results are sensitive to many pathological changes in the body. Blood gas analysis refers to understanding the human respiratory function and acid-base balance status by measuring the pH of human blood and the gases dissolved in the blood (mainly including carbon dioxide and oxygen). The blood gas analysis results can directly reflect the lung ventilation function and its acid-base balance. Status, specifically including but not limited to arterial oxygen partial pressure, _CO2 partial pressure, etc.

Ventilation parameters can reflect the status of the ventilation equipment that provides mechanical ventilation to the ventilated subject, and further reflect whether the respiratory support that the ventilation equipment can provide in the current state matches the needs of the ventilated subject. The ventilation parameters may include control parameters of the ventilation device, and monitoring parameters for feedback adjustment of the control parameters. Exemplarily, ventilation parameters include, but are not limited to, tidal volume, respiratory rate, positive end-expiratory pressure, inspired oxygen concentration, and the like. Tidal volume is the amount of air inhaled or exhaled in each breath; respiratory rate represents the amount of air inhaled per unit time; positive end-expiratory pressure (PEEP) is a certain positive pressure maintained in the respiratory tract at the end of expiration, and its function is to avoid Early alveolar closure expands some alveoli that have lost their ventilation function due to exudation, atelectasis, etc., increasing the reduced functional residual volume to achieve the purpose of increasing blood oxygen; the inhaled oxygen concentration is the proportion of oxygen in the gas provided by the ventilation equipment volume percentage.

After obtaining the above ventilation-related information, the ventilation-related information is input into the ventilation analysis model to obtain the ventilation analysis results corresponding to the current ventilation mode. Since the ventilation analysis model needs to comprehensively analyze ventilation-related information over a period of time, the analysis results can be updated at regular intervals. The ventilation analysis results corresponding to the current ventilation mode at least include evaluation results obtained by evaluating the current ventilation mode, and the evaluation results are used to characterize whether the current ventilation mode is feasible for the ventilation subject. Furthermore, the ventilation analysis results corresponding to the current ventilation mode also include factors that affect the evaluation results.

Among them, the ventilation analysis model can be obtained by training on the basis of a network model with analysis and judgment capabilities. Generally speaking, the data type of the data used to train the network model is consistent with the data type of ventilation-related information. In the model training phase, ventilation analysis models for assisting decision-making can be generated based on expert knowledge base and artificial intelligence technologies such as decision trees, regression analysis of past data, CatBoost, XGBoost, and random forests.

Specifically, training data can be collected to build a training database. The training data can come from the medical record database. Each set of training data includes ventilation mode, ventilation-related information and corresponding treatment results. Treatment outcomes include failed outcomes, in which the patient's condition worsens or dies, or successful outcomes, in which the patient recovers or improves in condition. For example, a training database can be constructed for each ventilation mode to train the ventilation analysis model for each ventilation mode. By training the ventilation analysis model, after the ventilation-related information is input into the ventilation analysis model, the ventilation analysis model can Output the ventilation analysis results corresponding to the ventilation mode. Alternatively, a unified model can be trained so that after the current ventilation mode and ventilation-related information are input into the ventilation analysis model, the ventilation analysis model can output ventilation analysis results corresponding to the current ventilation mode.

The evaluation results of the current ventilation method output by the ventilation analysis model can be in various forms, as long as they can reflect whether the current ventilation method is appropriate. For example, the evaluation results output by the ventilation analysis model include the failure probability or success probability of the current ventilation mode. It can be understood that the sum of the failure probability and the success probability is 100%, and you can choose to display the failure probability or the success probability. Users can judge by themselves whether the failure probability or success probability meets expectations, or they can display the threshold of failure probability or success probability on the display interface to assist users in comparison. In some embodiments, failure probabilities above or below a preset threshold can also be displayed as different colors, or success probabilities above or below a preset threshold can be displayed as different colors, etc., so as to be more intuitive. Prompts the user on the feasibility of the current ventilation method.

In one embodiment, the evaluation result of the current ventilation mode includes a failure probability or a success probability of weaning from the current ventilation mode. The failure probability or success probability of weaning from the current ventilation mode represents the failure probability or success probability of weaning from the ventilation device at the current moment. In comparison, the failure probability or success probability of the current ventilation mode described above indicates that if Continuing to provide mechanical ventilation to the ventilated subject using the current ventilation method, the probability that the final treatment will fail (for example, the ventilated subject's condition worsens or dies) or the treatment will be successful (for example, the ventilated subject will recover). Outputting the failure probability or success probability of weaning from the current ventilation method can assist the user in judging whether weaning can currently be performed.

When the current ventilation method is an invasive ventilation method, the evaluation results of the current ventilation method may include the failure probability or success probability of extubation from the current ventilation method. Among them, extubation includes weaning from invasive ventilation, or switching from invasive ventilation to non-invasive ventilation or high-flow oxygen therapy that does not require an artificial airway. The failure probability or success probability of extubation from the current ventilation mode is the failure probability or success probability at the current moment. Outputting the failure probability or success probability of extubation from the current ventilation method can assist the user in judging whether extubation is currently possible and switching invasive ventilation to other ventilation methods that do not require artificial airway.

In the ventilation analysis method 100, the output ventilation analysis results also include factors that affect the evaluation results. Illustratively, the influencing factors on the assessment results include at least one of risk factors and beneficial factors of the assessment results. Outputting the assessment results together with risk factors or beneficial factors will help medical staff understand the reasons for the assessment results, troubleshoot hidden dangers, and increase the credibility of the assessment results. Among them, risk factors include factors that lead to the failure of the current ventilation method, and beneficial factors include factors that promote the success of the current ventilation method. Risk factors and benefit factors can be derived from ventilation-related information about the ventilated subject. For example, risk factors include physiological states or pathological states that lead to the failure of the current ventilation method, and beneficial factors include physiological states or pathological states that lead to the success of the current ventilation method.

Furthermore, the ventilation analysis results may also include the contribution of risk factors or beneficial factors to the assessment results. Refer to Figure 3, which shows the following risk factors of the current ventilation method: plateau pressure, tidal volume, heart rate, blood pressure, APACHE and PaO2; and the contribution of each risk factor to the evaluation results. As can be seen from Figure 3, the two most important factors that may cause the failure of the current ventilation method are plateau pressure and tidal volume. In other words, the input of plateau pressure and tidal volume largely leads to an increase in the failure probability of the current ventilation method output by the model. . Healthcare professionals can focus on the causes of poor plateau pressure and tidal volume measurements to improve the probability of success with the current ventilation method.

In one embodiment, when the evaluation result of the current ventilation mode does not meet the preset requirements, the ventilation analysis result may also include a recommended ventilation mode. For example, the failure probability or success probability corresponding to each ventilation mode can be obtained through a ventilation analysis model, and the ventilation mode with the lowest failure probability or the highest success probability is selected as the recommended ventilation mode. Recommended ventilation methods may include at least one. Outputting the recommended ventilation method can assist the user in deciding which ventilation method to switch the current ventilation method to.

Furthermore, the ventilation analysis results may also include the degree of recommendation of the recommended ventilation method. The recommendation level may be the recommendation level for all ventilation methods, the recommendation level for the optimal ventilation method, or the recommendation level for ventilation methods with a recommendation level higher than a threshold. Users can decide which ventilation method to use based on the recommendation level and subjective evaluation. For example, if the recommended degree of two ventilation methods is similar, the user can also choose to switch to a ventilation method with a lower degree of recommendation based on other external factors, and is not limited to only using the ventilation method with the highest degree of recommendation.

For example, if the current ventilation method is high-flow oxygen therapy and cannot meet the needs of the ventilation subjects, the recommendation level for non-invasive ventilation and invasive ventilation can be output to assist the user in deciding to switch from high-flow oxygen therapy to non-invasive. Ventilation mode or switch to invasive ventilation mode. For example, the degree of recommendation of each ventilation mode may be determined based on the success probability of each ventilation mode. If the current ventilation method is an invasive ventilation method and can meet the needs of the ventilation subject, and the ventilation analysis model analysis shows that the success probability of the non-invasive ventilation method or high-flow oxygen therapy method is higher than the threshold, then the results of the non-invasive ventilation method and high-flow oxygen therapy method can be output. The recommendation level of flow oxygen therapy mode helps users decide whether to switch from invasive ventilation mode to non-invasive ventilation mode or to switch to high flow oxygen therapy ventilation mode.

In one embodiment, the ventilation analysis results also include the probability of failure or success of ventilation using the recommended ventilation method, that is, assuming that the ventilated subject adopts the recommended ventilation method for ventilation, the probability of final treatment failure or success Probability. Outputting the failure probability or success probability of ventilation using the recommended ventilation method helps assist doctors to determine whether only switching the ventilation method is needed to ensure successful treatment. If the failure probability is still too high after switching to the recommended ventilation method, it is necessary The doctor takes other treatment methods promptly.

In one embodiment, the ventilation analysis results also include influencing factors of switching from the current ventilation mode to the recommended ventilation mode. For example, what factors prompt the ventilation analysis model to output ventilation analysis results that recommend switching from non-invasive ventilation mode to invasive ventilation mode, and what factors prompt the ventilation analysis model to output ventilation analysis results that recommend switching from non-invasive ventilation mode to invasive ventilation mode, etc. .

Furthermore, the influencing factors of switching from the current ventilation mode to the recommended ventilation mode also include risk factors that lead to failure in ventilation mode switching, and beneficial factors that lead to successful ventilation mode switching. Among them, switching failure mainly refers to the failure of the process of switching from an advanced ventilation mode to a low-level ventilation mode. For example, after switching from an invasive ventilation mode to a non-invasive ventilation mode, the non-invasive ventilation mode cannot maintain the breathing of the ventilated subject. Therefore, the risk factors that lead to the failure of ventilation mode switching may include risk factors that lead to the failure of the ventilation mode after switching, and the beneficial factors that lead to the success of ventilation mode switching may include the risk factors that lead to the success of the ventilation mode after switching.

For example, in addition to the analysis results for the ventilation mode, the ventilation analysis results may also include recommended ventilation modes. The classification basis of ventilation modes mainly includes conditions for triggering ventilation, conditions for limiting inspiratory flow rate, conditions for switching ventilation, etc. That is, the ventilation mode is the respiratory support strategy under each ventilation mode.

Exemplarily, ventilation modes include machine-controlled mode, autonomous mode and composite mode. Among them, the machine-controlled mode means that the ventilation equipment completely replaces the spontaneous breathing of the ventilated subject, specifically including volume-controlled mode, pressure-controlled mode, etc. In the autonomous mode, the breathing switching is determined by the spontaneous breathing of the ventilated subject, and the inspiratory trigger and inspiratory time depend on the ventilated subject itself. Autonomous mode mainly includes pressure support mode (CPAP). The composite mode combines the machine-controlled mode and the autonomous mode. It means that when the ventilated subject appears to breathe spontaneously, it will assist the ventilated subject to complete spontaneous breathing; if the ventilated subject does not breathe spontaneously, machine-controlled ventilation will be given. This mode can reduce the risk of spontaneous breathing of the ventilated subject. Ventilator versus.

Ventilation objects in different states are suitable for different ventilation modes. For example, if the ventilated subject recovers spontaneous breathing, it is recommended to switch from machine-controlled mode to spontaneous ventilation mode; if the ventilated subject has unstable breathing, it is recommended to use SIMV mode; for patients with severe ARDS, it is recommended to use volume-controlled ventilation mode. Of course, the factors considered by the ventilation analysis model are not limited to these, but can combine a variety of ventilation-related information to output ventilation mode recommendations. Compared with subjective judgment, the factors considered are more comprehensive.

In addition to outputting recommendations for ventilation modes, the ventilation mode of the ventilation device that provides ventilation for the ventilated object can also be automatically set to the recommended ventilation mode to achieve automatic switching of ventilation modes. For example, when the ventilation analysis method 100 is implemented in a ventilation device, after the ventilation device itself obtains the analysis results regarding the ventilation mode, its processor controls the automatic switching of the ventilation mode. When the ventilation analysis method 100 is implemented in other medical equipment such as a central station, the analysis results of the ventilation mode can be sent to the ventilation equipment through the network connection between the medical equipment. After the ventilation equipment receives the analysis results of the ventilation mode, it will be processed by it. Automatic switching of ventilation modes is achieved through device control.

In step S130, the manner of outputting the ventilation analysis results may include outputting the ventilation analysis results in real time. For example, ventilation analysis results such as failure probability or success probability of the current ventilation mode, failure probability or success probability of weaning from the current ventilation mode, etc. can be displayed on the display interface in real time, so that the display interface can refresh the latest ventilation analysis results in real time.

Alternatively, the manner of outputting the ventilation analysis results may include outputting the ventilation analysis results when the ventilation analysis results meeting the preset requirements are obtained. For example, the failure probability or success probability may be output when the failure probability of the current ventilation mode is higher than a preset threshold, or the success probability of the current ventilation mode is lower than the preset threshold. Alternatively, the resulting failure or success probabilities can be displayed in real time and an alert generated when the failure probability is above a preset threshold or the success probability is below a preset threshold. For another example, when the failure probability of the current ventilation method is higher than the preset threshold or the success probability is lower than the preset threshold, the recommended ventilation method is displayed; otherwise, other ventilation methods are not recommended.

In summary, the ventilation analysis method 100 of the embodiment of the present application uses a ventilation analysis model combined with various ventilation-related information to analyze and evaluate the currently adopted ventilation mode, and outputs the evaluation results of the current ventilation mode and its influencing factors, which can instantly Give objective and accurate suggestions to assist doctors in promptly switching ventilation methods when necessary.

On the other hand, the embodiment of the present application provides a medical device. Referring to Figure 4, the medical device 400 includes a memory 410, a processor 420 and a display 430. The memory 410 stores a computer program run by the processor 420. The computer program is When the processor 410 is running, the processor 410 executes the steps of the ventilation analysis method as described above to obtain the ventilation analysis results, and the display 430 is used to display the ventilation analysis results.

The medical device 400 in the embodiment of the present application includes, but is not limited to, any one of a monitor, a local central station, a remote central station, a cloud service system, a mobile terminal, or a combination thereof. The medical device 400 may be a portable medical device, a transport medical device, a mobile medical device, or the like.

In one embodiment, medical device 400 includes a ventilation device. Ventilation equipment includes ventilators, anesthesia machines and other medical equipment with ventilation functions. Ventilation equipment is used to replace, control or change the physiological breathing of the ventilated subject, improve the respiratory function of the ventilated subject and reduce the respiratory consumption of the ventilated subject by increasing lung ventilation. In some embodiments, the ventilation device may be a ventilation device with non-invasive ventilation, invasive ventilation, and high-flow oxygen therapy functions.

The medical device 400 may also include a monitor, which is used to monitor patient monitoring parameters in real time. The monitor may include a bedside monitor, a wearable monitor, etc. The medical device 400 may also include a central station for receiving monitoring data sent by medical devices such as monitors and performing centralized monitoring of the monitoring data.

In some embodiments, the central station and other medical equipment can form an interconnection platform through BeneLink to realize data communication between the central station and other medical equipment. For example, the central station can access monitoring data monitored by a monitor. In some other embodiments, the central station and other medical equipment can also establish data connections through communication modules, including but not limited to Wifi, Bluetooth or 2G, 3G, 4G, 5G and other communication modules of mobile communication.

The processor 420 of the medical device 400 can be a central processing unit (CPU), or other general-purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC) ), field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The processor 420 is the control center of the medical device 400 and connects various parts of the entire medical device 400 using various interfaces and lines.

The display 430 is used to provide visual display output to the user. Specifically, the display 430 can be used to provide a visual display interface for the user, including but not limited to a monitoring interface, an operation interface, a parameter setting interface, an alarm interface, etc. For example, the display 430 can be implemented as a touch display, or have an input panel. The display 430, that is, the display 430 may serve as an input/output device.

Medical device 400 also includes memory 410 . The memory 410 is used to store data of ventilation objects associated with the medical device 400. The memory 410 also stores program codes, and the processor 420 is configured to call the program codes in the memory 410 to execute the steps of the ventilation analysis method 100 described above. The memory 410 may mainly include a program storage area and a data storage area, where the program storage area may store an operating system, application programs required for multiple functions, and the like. In addition, the memory 410 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart memory card, secure digital card, flash memory card, multiple disk storage devices, flash memory devices, or other volatile solid-state storage devices.

When the medical device 400 is a ventilation device, the medical device 400 further includes a ventilation unit for providing mechanical ventilation to the ventilated subject. Exemplarily, the ventilation unit at least includes an air source interface and an air path. The air source interface is connected to the air source. The air source may include an external air source such as a central air supply system in a hospital, or may also include an external air compressor or a built-in air supply. turbine, etc.; the air path includes the inspiratory branch and the expiratory branch. Among them, the inhalation branch is used to manage the inhalation behavior of the ventilation object, and can provide gas with required oxygen concentration and flow rate for the ventilation object. The expiratory branch is used to manage the exhalation behavior of the ventilated subject and can receive the gas exhaled by the ventilated subject. In the suction branch, the end far away from the ventilation object is connected to the air source through the air source interface, and the supply gas provided by the air source is obtained and supplied to the ventilation object at the other end of the suction branch. The supply gas may be oxygen or a mixture of air and oxygen. A flow adjustment device can also be provided on the suction branch to provide a required flow rate of gas; the flow adjustment device includes an electromagnetic proportional valve, but is not limited to this. A pressure regulating device can also be provided on the suction branch to provide gas at a required pressure; the pressure regulating device includes a pressure regulating valve, but is not limited to this. In some embodiments, medical device 400 also includes a sensor. The sensor and the processor 420 can be connected through a wired communication protocol or a wireless communication protocol, so that data can be exchanged between the sensor and the processor 420 . Wireless communication technologies include but are not limited to: various generations of mobile communication technologies (2G, 3G, 4G and 5G), wireless networks, Bluetooth, ZigBee, ultra-wideband UWB, NFC, etc. Specifically, the sensor is used to collect the patient's physiological data, such as vital sign parameters and ventilation parameters. In some embodiments, the sensor may be independently disposed outside the medical device 400 and detachably connected to the medical device 400 . The processor 420 is also used to perform data processing on the monitoring data signals from the sensors. In some other embodiments, the medical device 400 may not include a sensor, and the medical device 400 may receive monitoring data collected by an external monitoring accessory through a communication module.

When the medical device 400 is a ventilation device, the sensor at least includes a flow sensor disposed in the gas path for measuring the flow signal of the gas in the gas path. The processor 420 can control the flow adjustment device according to the flow value detected by the flow sensor to achieve precise control of the flow. The sensor also includes a pressure sensor for detecting a pressure signal, the pressure sensor includes a pressure sensor for detecting the gas pressure at the gas source, and a pressure sensor for monitoring a pressure signal reflecting the inspiratory effort of the ventilated subject, reflecting the pressure of the ventilated subject's inspiratory effort. Signals include intrapulmonary pressure signal, airway pressure signal, esophageal pressure signal, transdiaphragmatic pressure signal, etc.

Medical device 400 may also include a communication module coupled to processor 420 . In some embodiments, the medical device 400 can establish data communication with a third-party device through a communication module. The processor 420 also controls the communication module to obtain data from the third-party device, or send monitoring data collected by the sensor to the third-party device. Communication modules include but are not limited to WiFI, Bluetooth, NFC, ZigBee, ultra-wideband UWB or 2G, 3G, 4G, 5G and other mobile communication modules. In some other embodiments, the medical device 400 can also establish a connection with a third-party device through a cable. Third-party devices include other medical devices. Third-party devices can also be cloud service systems or mobile terminals such as mobile phones, tablets, and personal computers.

In some embodiments, the medical device 400 also includes an alarm module connected to the processor 420 for outputting alarm prompts so that medical staff can perform corresponding rescue measures. Alarm modules include but are not limited to alarm lights, alarm speakers, etc. The alarm information can be displayed on the display, the alarm light can flash to alert medical staff, or the alarm information can be played through the alarm speaker.

In order to implement user interface and data exchange, in addition to the display 430, the medical device 400 may also include other input/output devices connected to the processor 420, including but not limited to input devices such as keyboards, mice, touch screens, and remote controls. , and output devices including but not limited to printers, speakers, etc.

It should be understood that FIG. 4 is only an example of components included in the medical device 400 and does not constitute a limitation on the medical device 400. The monitoring device 400 may include more or less components than those shown in FIG. 4, or a combination of certain components. Some components, or different components, such as the medical device 400 may also include a power module, a positioning and navigation device, a printing device, etc.

The medical device 400 in the embodiment of the present application is used to implement the ventilation analysis method 100 mentioned above, and therefore also has similar advantages.

Referring to Figure 2 below, another aspect of the embodiment of the present application provides a ventilation analysis method 200 for a central station. The ventilation analysis method 200 is generally similar to the ventilation analysis method 100, except that the ventilation analysis method 100 can be implemented in A variety of medical devices, while the Ventilation Analysis Method 200 is dedicated to central stations. The central station can be interconnected with a variety of medical devices, making it easier to obtain ventilation-related information from a variety of medical devices; and the central station can be interconnected with multiple ventilators to provide ventilation analysis results for multiple ventilated objects. As shown in Figure 2, the ventilation analysis method 200 includes the following steps:

In step S210, ventilation-related information of the ventilation object is obtained from the ventilation equipment and/or third-party equipment that is communicatively connected to the central station. The ventilation-related information at least includes basic information, medical information, physiological data and ventilation parameters of the ventilation object. For details of this step, reference may be made to step S110 in the ventilation analysis method 100 . For example, the central station can obtain ventilation parameters from a ventilation device that provides mechanical ventilation to a ventilated subject; obtain vital sign parameters of the same ventilated subject from a monitor that is communicatively connected to the central station; extract medical information of the ventilated subject from a clinical information system and Basic Information.

In step S220, the ventilation-related information is input into the ventilation analysis model to obtain ventilation analysis results corresponding to the current ventilation mode. The ventilation analysis results at least include evaluation results of the current ventilation mode. For details of this step, refer to step S120 in the ventilation analysis method 100 . The difference is that the ventilation analysis results of the ventilation analysis method 100 at least include the evaluation results obtained by evaluating the current ventilation mode and the influencing factors of the evaluation results, and the ventilation analysis method 200 may only include the evaluation results obtained by evaluating the current ventilation mode.

In step S230, the ventilation analysis result is sent to the ventilation device and/or a third-party device. The third-party device may be a third-party device that provides ventilation-related information, or may be another third-party device.

The ventilation analysis method 200 analyzes and evaluates the currently adopted ventilation method through a ventilation analysis model and a variety of ventilation-related information, and can give objective and accurate suggestions to assist doctors in timely switching ventilation methods when necessary. Furthermore, the ventilation analysis method 200 is implemented in a central station, which makes it easier to aggregate ventilation-related information on ventilation objects from multiple sources. For more specific details of the ventilation analysis method 200, please refer to the relevant description of the ventilation analysis method 100, and will not be described again here.

Another aspect of the embodiment of the present application provides a central station for implementing the above ventilation analysis method 200. Referring to Figure 5, the central station 500 includes a memory 510, a processor 520 and a communication unit 530. A computer program run by the processor 520 is stored on the memory 510. The computer program executes the steps of the ventilation analysis method 200 when run by the processor 520. The ventilation analysis results are obtained. The communication unit 530 is used to send the ventilation analysis results obtained by the processor 520 to the ventilation equipment that is communicatively connected to the central station. The ventilation equipment is used to provide mechanical ventilation for the ventilation object. The ventilation analysis results are for the ventilation equipment. Ventilation analysis results for currently used ventilation methods. Central stations may include local central stations or remote central stations. The central station connects the monitoring equipment and ventilation equipment in one department or multiple departments through the network to achieve the purpose of real-time centralized monitoring and massive data storage. For example, the central station stores monitoring data, basic patient information, medical history information, diagnostic information, etc., but is not limited to this.

Referring to Figure 6, an embodiment of the present application also provides a medical system 600. The medical system 600 includes a ventilation device 610 and a central station 620. The central station 620 may be the central station 500 as described above, and is used to execute the ventilation analysis method 100 or the ventilation analysis method 200 to obtain ventilation analysis results. The ventilation equipment 610 is communicatively connected with the central station 620 to receive and display the ventilation analysis results sent by the central station 620. The central station 620 can be communicatively connected with multiple ventilation devices 610 and other devices such as monitors. The ventilation analysis results obtained by the central station 620 can also be displayed on the display interface of the central station 620 itself. For specific details of the ventilation analysis method performed by the central station 620, please refer to the relevant description of the ventilation analysis method 100 or the ventilation analysis method 200 above, and will not be described again here.

In summary, according to the ventilation analysis method, medical equipment, central station and medical system of the embodiments of the present application, the ventilation analysis model is combined with a variety of ventilation-related information to analyze and evaluate the currently adopted ventilation methods, and can provide objective and accurate results in real time. It is recommended that the assistant doctor switch the ventilation mode in time when necessary.

Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above-described example embodiments are exemplary only, and are not intended to limit the scope of the application thereby. Various changes and modifications can be made therein by those of ordinary skill in the art without departing from the scope and spirit of the present application. All such changes and modifications are intended to be included within the scope of the application as claimed in the appended claims.

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 with 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. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or can be integrated into another device, or some features can be ignored, or not implemented.

In the instructions provided here, a number of specific details are described. However, it is understood that embodiments of the present application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this description.

Similarly, it should be understood that in the description of the exemplary embodiments of the present application, in order to streamline the present application and aid in the understanding of one or more of the various inventive aspects, various features of the present application are sometimes grouped together into a single embodiment, FIG. , or in its description. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as the corresponding claims reflect, the inventive concept lies in solving a corresponding technical problem with less than all features of a single disclosed embodiment. Thus, the claims following the Detailed Description are hereby expressly incorporated into this Detailed Description, with each claim standing on its own as a separate embodiment of this application.

It will be understood by those skilled in the art that all features disclosed in this specification (including the accompanying claims, abstract and drawings) and all features of any method or apparatus so disclosed may be used in any combination, except where the features are mutually exclusive. Processes or units are combined. Each feature disclosed in this specification (including accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features of different embodiments are meant to be within the scope of the present application. within and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

Various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art should understand that a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some modules according to embodiments of the present application. The present application may also be implemented as a device program (eg, computer program and computer program product) for performing part or all of the methods described herein. Such a program implementing the present application may be stored on a computer-readable medium, or may be in the form of one or more signals. Such signals may be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The application may be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the element claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, third, etc. does not indicate any order. These words can be interpreted as names.

The above are only specific implementation modes or descriptions of specific implementation modes of the present application. The protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily Any changes or substitutions that come to mind should be covered by the protection scope of this application. The protection scope of this application shall be subject to the protection scope of the claims.

Claims (25)

1. A ventilation analysis method, characterized by including:

   Obtaining ventilation-related information of the ventilation subject, the ventilation-related information at least includes basic information, medical information, physiological data and ventilation parameters of the ventilation subject;

   Input the ventilation-related information into the ventilation analysis model to obtain the ventilation analysis results corresponding to the current ventilation mode. The ventilation analysis results at least include the evaluation results obtained by evaluating the current ventilation mode and the influencing factors of the evaluation results;

   Output the ventilation analysis results.
2. A ventilation analysis method, characterized in that the method is used in a central station and includes:

   Obtain ventilation-related information of the ventilation object from the ventilation equipment and/or third-party equipment communicatively connected to the central station, where the ventilation-related information at least includes basic information, medical information, physiological data and ventilation parameters of the ventilation object;

   Input the ventilation-related information into the ventilation analysis model to obtain ventilation analysis results corresponding to the current ventilation mode, where the ventilation analysis results at least include evaluation results of the current ventilation mode;

   Send the ventilation analysis results to the ventilation equipment and/or third-party equipment.
3. The method according to claim 1, wherein the influencing factors include risk factors and/or beneficial factors of the assessment results.
4. The method according to claim 3, wherein the risk factors include physiological states and/or pathological states that lead to the failure of the current ventilation method, and the beneficial factors include physiological states and/or pathological states that lead to the success of the current ventilation method. .
5. The method according to claim 3, wherein the ventilation analysis results further include the contribution of the risk factors and/or the beneficial factors to the evaluation results.
6. The method according to claim 1 or 2, wherein the current ventilation mode includes a high-flow oxygen therapy mode, a non-invasive ventilation mode or an invasive ventilation mode.
7. The method according to claim 1 or 2, characterized in that the evaluation result includes the failure probability or success probability of the current ventilation mode.
8. The method according to claim 1 or 2, characterized in that the evaluation result includes a failure probability or a success probability of weaning from the current ventilation mode.
9. The method according to claim 1 or 2, characterized in that when the current ventilation mode is an invasive ventilation mode, the evaluation result includes a failure probability or a success probability of extubation from the current ventilation mode.
10. The method according to claim 1 or 2, characterized in that when the evaluation result of the current ventilation mode does not meet the preset requirements, the ventilation analysis result also includes a recommended ventilation mode.
11. The method according to claim 10, wherein the ventilation analysis result further includes the recommendation degree of the recommended ventilation mode.
12. The method according to claim 10, wherein the ventilation analysis result further includes a failure probability or a success probability of ventilation using the recommended ventilation method.
13. The method according to claim 10, wherein the ventilation analysis results further include influencing factors of switching from the current ventilation mode to the recommended ventilation mode.
14. The method according to claim 13, wherein the influencing factors include risk factors that lead to failure of ventilation mode switching, and/or beneficial factors that lead to successful ventilation mode switching.
15. The method according to claim 1 or 2, characterized in that the ventilation analysis results also include recommended ventilation modes, and the ventilation modes include machine-controlled mode, autonomous mode and composite mode.
16. The method according to claim 15, further comprising:

    The ventilation mode of the ventilation device providing ventilation to the ventilated subject is automatically set to the recommended ventilation mode.
17. The method according to claim 1 or 2, wherein the basic information includes at least one of the age, gender, height and weight of the ventilation subject.
18. The method according to claim 1 or 2, characterized in that the medical information includes at least one of the following: diagnosis results of the ventilated subject, past medical history, acute physiology and chronic health score, sequential organ failure score, consciousness status, vasoactive medication dosage, and sedation score.
19. The method according to claim 1 or 2, characterized in that the physiological data includes at least one of the following: physiological data collected by a ventilation device that provides ventilation for the ventilation subject and reflecting the spontaneous breathing effort of the ventilation subject, ventilation Physiological data collected by the equipment reflecting the respiratory system status of the ventilation subject, vital sign parameters collected by the monitoring equipment associated with the ventilation subject, and inspection information of the ventilation subject.
20. The method according to claim 19, wherein the vital sign parameters include at least one of the following: heart rate, respiratory rate, blood pressure, transcutaneous finger pulse oxygen saturation, and end-tidal carbon dioxide partial pressure.
21. The method according to claim 19, wherein the test information includes at least one of the following: blood routine results and blood gas results.
22. The method according to claim 1, wherein the ventilation parameters include at least one of the following: tidal volume, respiratory rate, positive end-expiratory pressure, and inspired oxygen concentration.
23. A medical device, characterized in that the medical device includes a memory, a processor and a display, and a computer program run by the processor is stored on the memory, and the computer program is executed when run by the processor. The steps of the ventilation analysis method according to any one of claims 1 and 3-22 are to obtain the ventilation analysis results, and the display is used to display the ventilation analysis results.
24. A central station, characterized in that the central station includes a memory, a processor and a communication unit. The memory stores a computer program run by the processor. When the computer program is run by the processor Execute the steps of the ventilation analysis method according to any one of claims 2 and 6-22 to obtain ventilation analysis results, and the communication unit is used to send the ventilation analysis results obtained by the processor to the central station. Communication connected ventilation equipment.
25. A medical system, characterized in that the medical system includes a ventilation device and a central station as claimed in claim 24, and the ventilation device is communicatively connected to the central station to receive and display information issued by the central station. The ventilation analysis results.

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