Extracorporeal diaphragm pacing diagnosis and treatment effect evaluation method and system

Abstract

The invention relates to the technical field of diagnosis and treatment effect evaluation, in particular to an in-vitro diaphragm pacing diagnosis and treatment effect evaluation method and system. The method comprises the following steps: acquiring diagnosis and treatment information of a BPD child patient and physiological data before and after EDP diagnosis and treatment; according to the diagnosis and treatment information, the individual function level of the BPD child patient is determined; according to the physiological data and the individual function level, determining respiratory muscle function change, diaphragm function change and sputum excretion ability change of the BPD child patient; based on the respiratory muscle function change, the diaphragm function change and the sputum excretion capacity change, the EDP diagnosis and treatment effect is comprehensively evaluated. Evaluation deviation caused by neglecting individual factors is eliminated, and the evaluation result can reflect the overall physiological state of the child patient more truly. And the one-sidedness of subjective clinical observation is avoided. Based on the respiratory muscle function change, the diaphragm function change and the sputum excretion capacity change, the EDP diagnosis and treatment effect is comprehensively evaluated, and the defects that a multi-dimensional integration mechanism is lacked and a quantifiable result cannot be provided are overcome.

Description

Technical Field

[0001] The present application relates to the technical field of diagnosis and treatment effect evaluation, and in particular to a method and system for evaluating the diagnosis and treatment effect of external diaphragm pacing. Background Art

[0002] External diaphragmatic pacing (EDP), a non-invasive neuromodulation technology, has demonstrated significant efficacy in the treatment of chronic respiratory failure, heart failure, and sleep-disordered breathing in adults in recent years. With its expanded clinical application, EDP has gradually gained attention in pediatrics, particularly in respiratory rehabilitation for children with bronchopulmonary dysplasia (BPD). Children with BPD suffer from structural lesions such as long-term atelectasis and bullae, leading to a flattened diaphragm, disuse atrophy, and sputum dysfunction, creating a vicious cycle of "decreased diaphragmatic function and worsening respiratory failure." In theory, EDP could break this cycle by enhancing diaphragmatic contraction efficiency and improving cough motivation.

[0003] However, existing evaluation methods often adopt unified standards and focus on a single or a few macro indicators for evaluation, resulting in poor universality of evaluation results and limited reference value, which restricts the precise application and efficacy optimization of EDP technology in the treatment of children with BDP. Summary of the Invention

[0004] The present application provides a method and system for evaluating the diagnostic and therapeutic effects of external diaphragm pacing to solve the above-mentioned problems.

[0005] In a first aspect, the present application provides a method for evaluating the diagnostic and therapeutic effects of external diaphragm pacing, the method comprising: Obtain the diagnosis and treatment information of children with BPD and their physiological data before and after EDP diagnosis and treatment; determining the individual functional level of the child with BPD based on the diagnosis and treatment information; Determining changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level; Based on the changes in respiratory muscle function, diaphragmatic function and expectoration ability, the EDP diagnosis and treatment effect is comprehensively evaluated.

[0006] Through this program, the diagnosis and treatment information of children with BPD and their physiological data before and after EDP diagnosis and treatment are obtained, avoiding assessment bias caused by missing or inconsistent data and improving the repeatability and quantification of the assessment. Based on the diagnosis and treatment information, the individual functional level of children with BPD is determined, eliminating the assessment bias caused by ignoring individual factors, so that the assessment results more truly reflect the overall physiological status of the children. Based on physiological data and individual functional levels, the changes in respiratory muscle function, diaphragm function and expectoration ability of children with BPD are determined to reflect the improvement of respiratory muscle strength, avoid the one-sidedness of subjective clinical observations, capture the overall impact of EDP on diaphragm function, and correlate the cough-inducing effect of EDP to avoid one-sidedness of the assessment. Based on the changes in respiratory muscle function, diaphragm function and expectoration ability, the diagnosis and treatment effects of EDP are comprehensively evaluated to eliminate the defects of lacking a multi-dimensional integration mechanism and being unable to provide quantifiable results.

[0007] Optionally, determining the individual functional level of the child with BPD based on the diagnosis and treatment information includes: Analyze the diagnosis and treatment information to determine the child's age, BPD severity level, number of comorbidities, and baseline lung function indicators; Obtaining BPD onset information; and matching the age of the child, the basic lung function index, the BPD severity grade, and the number of comorbidities with the weights of their respective impact on the condition of the BPD child based on the BPD onset information; Based on the BPD onset information, the child's age and the basic lung function index are converted into positive z-score values ​​respectively; The BPD severity grade and the number of comorbidities were converted into negative z-score values; The individual functional level of the BPD child is calculated and determined based on the disease impact weight, the positive z-score value, and the negative z-score value.

[0008] Through this solution, diagnosis and treatment information is parsed to determine the child's age, BPD severity grade, number of comorbidities, and baseline lung function indicators, generating a structured, numerical parameter set to ensure direct operation and avoid missing or ambiguous parameters. BPD incidence information is obtained to ensure the reliability and adaptability of the assessment. Based on BPD incidence information, the weights of the child's age, baseline lung function indicators, BPD severity grade, and number of comorbidities on the BPD child's condition are matched, and standardized weights are generated for weighted calculations to ensure that individual factors are accurately weighted in the assessment. Based on BPD incidence information, the child's age and baseline lung function indicators are converted into positive z-score values, making different parameters such as the child's age and baseline lung function indicators comparable and strengthening the contribution direction of the positive parameters. The z-score eliminates dimensional differences, and the positive conversion ensures parameter direction consistency. The higher the values ​​of the child's age and baseline lung function indicators, the more favorable it is. The BPD severity grade and number of comorbidities were converted to negative z-score values, making them comparable and emphasizing the contribution of negative parameters. The z-score eliminates dimensional differences, and the negative conversion ensures directional consistency. Higher values ​​for BPD severity grade and number of comorbidities are associated with a more unfavorable outcome. The individual functional level of children with BPD was calculated based on the disease impact weight, positive z-score values, and negative z-score values. This was used to analyze the effectiveness of EDP diagnosis and treatment, ensuring that the results reflect the individualized comprehensive status.

[0009] Optionally, based on the BPD onset information, converting the child's age and the basic lung function index into positive z-score values ​​respectively includes: Based on the BPD onset information, determine the mean age and standard deviation of BPD onset age; Determining the conversion of the positive z-score value corresponding to the age of the child according to the mean age of BPD onset and the age standard deviation; Based on the BPD onset information, the mean and standard deviation of lung function indicators of children with the same period were determined; Determine the conversion of the positive z-score value corresponding to the basic pulmonary function index according to the pulmonary function index mean and the pulmonary function standard deviation.

[0010] Through this solution, based on BPD onset information, the mean age and standard deviation of BPD onset are determined, eliminating assessment bias caused by age developmental differences and ensuring that the age values ​​of children of different months can be fairly compared. Based on the mean age and standard deviation of BPD onset, the conversion of positive z-score values ​​corresponding to the child's age is determined to eliminate the problem of incomparable absolute respiratory function values ​​in children of different months. Based on BPD onset information, the mean and standard deviation of lung function indicators for children of the same period are determined to eliminate the reliance on the absolute values ​​of individual indicators in the assessment. Based on the mean and standard deviation of lung function indicators, the conversion of positive z-score values ​​corresponding to basic lung function indicators is determined to make the lung function values ​​of children of different ages comparable. At the same time, the weights are optimized for EDP treatment needs to improve analysis accuracy.

[0011] Optionally, determining changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level includes: Analyze the physiological data to determine the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment; The rate of change of respiratory muscle strength before and after treatment was determined based on the maximum inspiratory pressure and maximum expiratory pressure before and after treatment; Correcting the respiratory muscle strength change rate according to the individual functional level to determine the respiratory muscle function change of the BPD child; Analyzing the physiological data to determine the diaphragm thickness and diaphragm movement range before and after diagnosis and treatment; According to the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment are determined; Determine the diaphragm function changes of the BPD children based on the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment; Analyzing the physiological data to determine the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within a preset time period before and after diagnosis and treatment; The basal change rate of sputum discharge was determined based on the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within the preset time period.

[0012] Through this program, physiological data is analyzed to determine the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment, eliminating the problem of difficulty in quantifying changes in respiratory muscle function. Based on the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment, the rate of change of respiratory muscle strength before and after diagnosis and treatment is determined, and the difference in respiratory muscle strength is converted into a comparable standardized indicator, eliminating the problem of high noise in the data of changes in respiratory muscle function. According to the individual functional level, the rate of change of respiratory muscle strength is corrected to determine the changes in respiratory muscle function of children with BPD, eliminating the problem of lack of personalized assessment mechanism and ensuring that the change value of respiratory muscle function truly reflects the specific effect of EDP. Physiological data is analyzed to determine the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, eliminating the problem of difficulty in quantifying changes in diaphragm function and avoiding the one-sidedness of relying on imaging observations. Based on the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, the rate of change of diaphragm thickness and diaphragm movement before and after diagnosis and treatment are determined, eliminating the problem of not being able to capture the overall impact of EDP on diaphragm function. Based on the rate of change in diaphragm thickness and diaphragm movement before and after diagnosis and treatment, changes in diaphragm function in children with BPD are determined, eliminating the lack of a comprehensive assessment of diaphragm function changes and avoiding the inadequacy of focusing on a single parameter. Analyze physiological data to determine the peak cough flow rate before and after diagnosis and treatment, as well as the amount of sputum discharged during the preset time period before and after diagnosis and treatment, ensuring that the data can serve the calculation of the rate of change and avoiding the one-sidedness of relying on simple records. Based on the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged during the preset time period, the basic rate of change in sputum discharge is determined, providing a complete quantitative value of the change in sputum discharge ability for the EDP diagnosis and treatment effect.

[0013] Optionally, determining the basal change rate of sputum discharge based on the peak cough flow rate before and after diagnosis and treatment and the sputum discharge volume within a preset period of time includes: Analyzing the changes in diaphragmatic function to determine the diaphragmatic expectoration coordination level; The sputum discharge basal change rate is determined based on the diaphragmatic sputum discharge coordination level, the cough peak flow rate before and after diagnosis and treatment, and the sputum discharge volume within a preset time period.

[0014] This protocol analyzes changes in diaphragmatic function and determines the level of diaphragmatic synergy in expectoration, avoiding subjective assessments and making the quantitative basis for expectoration efficiency more reliable and repeatable. The baseline rate of change in expectoration is determined based on the level of diaphragmatic synergy in expectoration, peak cough velocity before and after diagnosis and treatment, and sputum output within a preset time period. This not only reflects direct changes in coughing and sputum output but also captures the diaphragm's synergistic effect on expectoration, achieving comprehensive quantification of expectoration efficiency and providing repeatable evaluation results for EDP diagnosis and treatment effectiveness.

[0015] Optionally, matching the weights of the child's age and the basic lung function index on the condition of the BPD child based on the BPD onset information includes: Analyze the BPD incidence information and determine the monthly age distribution data of the affected group; Analyzing the monthly age distribution data and the age of the child to determine the skewness of the monthly age distribution; Determining the weight of the effect of the child's age on the condition of the BPD child according to the skewness of the monthly age distribution; Analyze the BPD onset information and determine the median lung function of children in the same period; Obtain functional baseline values ​​of healthy lung function; The weight of the impact of the basic lung function index on the condition of the BPD child is determined based on the median lung function of the children in the same period and the functional baseline value.

[0016] Through this solution, BPD incidence information is analyzed and the monthly age distribution data of the diseased group is determined. The monthly age distribution data and the age of the children are analyzed to determine the skewness of the monthly age distribution, ensuring that the group age distribution pattern is accurately captured to reflect the trend of the impact of the group distribution on the individual condition. Based on the skewness of the monthly age distribution, the weight of the impact of the child's age on the condition of BPD children is determined, and directly used for the overall calculation of the EDP diagnosis and treatment effect. The BPD incidence information is analyzed to determine the median lung function of children in the same period, ensuring that the weight of the basic lung function indicators is determined based on group data. The functional baseline value of healthy lung function is obtained to enhance the objectivity of the assessment. Based on the median lung function and functional baseline value of children in the same period, the weight of the impact of the basic lung function indicators on the condition of BPD children is determined, which is used for the overall calculation of the EDP diagnosis and treatment effect, realizing the parallel matching of the two weights.

[0017] Optionally, before obtaining the physiological data of the BPD child before and after receiving EDP diagnosis and treatment, the method further includes: Determine the diagnostic and treatment equipment based on the age of the child; Based on the age of the child, analyze and determine the difficulty of diagnosis and treatment and the condition of the child during the diagnosis and treatment process; Determine auxiliary diagnosis and treatment methods based on the condition of the child and the difficulty of diagnosis and treatment.

[0018] This solution determines the diagnostic and treatment equipment based on the patient's age, improving the accuracy and safety of EDP stimulation and avoiding invalid data due to device mismatch. Based on the patient's age, the difficulty of diagnosis and treatment and the patient's condition during treatment are analyzed and determined to reduce unexpected events during EDP treatment and prevent data loss due to poor compliance. Auxiliary diagnostic and treatment methods are determined based on the patient's condition and the difficulty of diagnosis and treatment to avoid data bias caused by the patient's agitation.

[0019] Optionally, before obtaining the physiological data of the BPD child before and after receiving EDP diagnosis and treatment, the method further includes: Determine the degree of compliance with instructions based on the age of the child; Determine the difficulty of inducing cough based on the child's condition; determining cough assistance means according to the degree of compliance with the instruction and the difficulty of inducing the cough; Based on the age and medical information of the child, the cough stimulation frequency and the concentration of the cough irritant in the cough assistive means are determined.

[0020] Through this program, the degree of compliance with instructions is determined according to the age of the child, and the selection of personalized auxiliary means is guided to avoid incomplete data collection due to the child's non-cooperation. According to the child's condition, the difficulty of cough induction is determined, the cough induction process is optimized, and the effectiveness of EDP treatment is ensured. According to the degree of compliance with instructions and the difficulty of cough induction, cough auxiliary means are determined to enhance the induction effect of cough reflex, thereby improving the integrity and reliability of physiological data collection. Based on the child's age and diagnosis and treatment information, the cough stimulation frequency and cough irritant concentration in the cough auxiliary means are determined to achieve refined setting of EDP parameters, optimize cough induction intensity, ensure personalized treatment process, and thus improve the accuracy and repeatability of data collection.

[0021] Optionally, matching the weights of the child's age, the basic lung function index, the BPD severity grade, and the number of comorbidities on the condition of the BPD child based on the BPD onset information includes: According to the monthly age distribution data, matching the weight of the impact of the child's age on the condition of the BPD child; Analyzing the physiological data to determine the real-time fluctuation amplitude of the blood oxygen saturation of the BPD child; According to the real-time fluctuation amplitude and the BPD onset information, the weights of the basic lung function index and the number of comorbidities affecting the condition of the BPD child are matched; According to the age of the child, the real-time fluctuation amplitude and the BPD onset information, the BPD severity grade is matched with the weight of the condition of the BPD child.

[0022] Through this solution, the weight of the impact of the child's age on the BPD child's condition is matched based on the monthly age distribution data, achieving quantitative assignment of the age factor and reflecting the differentiated impact of age on the condition. Physiological data is analyzed to determine the real-time fluctuation amplitude of the blood oxygen saturation of BPD children, converting dynamic physiological changes into calculable fluctuation parameters to eliminate subjective judgment bias. Based on the real-time fluctuation amplitude and BPD onset information, the weight of the impact of basic lung function indicators and the number of comorbidities on the condition of BPD children is matched, achieving real-time quantification of the impact of lung function on the condition, so that the contribution of the number of comorbidities to the condition is dynamically adjusted with blood oxygen stability. Based on the child's age, real-time fluctuation amplitude and BPD onset information, the weight of the impact of BPD severity grade on the condition of BPD children is matched to avoid the one-sidedness of a single grading standard.

[0023] In a second aspect, the present application provides a method and system for evaluating the diagnostic and therapeutic effects of external diaphragm pacing, the system comprising: The information acquisition module is used to obtain the diagnosis and treatment information of children with BPD and their physiological data before and after receiving EDP diagnosis and treatment; a level determination module, configured to determine the individual functional level of the child with BPD based on the diagnosis and treatment information; a change analysis module, configured to determine changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level; The effect evaluation module is used to comprehensively evaluate the EDP diagnosis and treatment effect based on the changes in the respiratory muscle function, the diaphragm function and the expectoration ability.

[0024] Optionally, when the level determination module determines the individual functional level of the BPD child based on the diagnosis and treatment information, it is configured to: Analyze the diagnosis and treatment information to determine the child's age, BPD severity level, number of comorbidities, and baseline lung function indicators; Obtaining BPD onset information; and matching the age of the child, the basic lung function index, the BPD severity grade, and the number of comorbidities with the weights of their respective impact on the condition of the BPD child based on the BPD onset information; Based on the BPD onset information, the child's age and the basic lung function index are converted into positive z-score values ​​respectively; The BPD severity grade and the number of comorbidities were converted into negative z-score values; The individual functional level of the BPD child is calculated and determined based on the disease impact weight, the positive z-score value, and the negative z-score value.

[0025] Optionally, when the level determination module converts the child's age and the basic lung function index into positive z-score values ​​based on the BPD onset information, it is used to: Based on the BPD onset information, determine the mean age and standard deviation of BPD onset age; Determining the conversion of the positive z-score value corresponding to the age of the child according to the mean age of onset of BPD and the standard deviation of the age; Based on the BPD onset information, the mean and standard deviation of lung function indicators of children with the same period were determined; Determine the conversion of the positive z-score value corresponding to the basic pulmonary function index according to the pulmonary function index mean and the pulmonary function standard deviation.

[0026] Optionally, when the change analysis module determines the changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level, it is configured to: Analyze the physiological data to determine the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment; The rate of change of respiratory muscle strength before and after treatment was determined based on the maximum inspiratory pressure and maximum expiratory pressure before and after treatment; Correcting the respiratory muscle strength change rate according to the individual functional level to determine the respiratory muscle function change of the BPD child; Analyzing the physiological data to determine the diaphragm thickness and diaphragm movement range before and after diagnosis and treatment; According to the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment are determined; Determine the diaphragm function changes of the BPD children based on the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment; Analyzing the physiological data to determine the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within a preset time period before and after diagnosis and treatment; The basal change rate of sputum discharge was determined based on the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within the preset time period.

[0027] Optionally, when determining the basal change rate of sputum discharge based on the peak cough flow rate before and after diagnosis and treatment and the sputum discharge volume within a preset period, the change analysis module is used to: Analyzing the changes in diaphragmatic function to determine the diaphragmatic expectoration coordination level; The sputum discharge basal change rate is determined based on the diaphragmatic sputum discharge coordination level, the cough peak flow rate before and after diagnosis and treatment, and the sputum discharge volume within a preset time period.

[0028] Optionally, the external diaphragm pacing diagnosis and treatment effect evaluation system further includes a weight determination module, which is used to: Analyze the BPD incidence information and determine the monthly age distribution data of the affected group; Analyzing the monthly age distribution data and the age of the child to determine the skewness of the monthly age distribution; Determining the weight of the effect of the child's age on the condition of the BPD child according to the skewness of the monthly age distribution; Analyze the BPD onset information and determine the median lung function of children in the same period; Obtain functional baseline values ​​of healthy lung function; The weight of the impact of the basic lung function index on the condition of the BPD child is determined based on the median lung function of the children in the same period and the functional baseline value.

[0029] Optionally, the external diaphragm pacing diagnosis and treatment effect evaluation system further includes a diagnosis and treatment means determination module, which is used to: Determine the diagnostic and treatment equipment based on the age of the child; Based on the age of the child, analyze and determine the difficulty of diagnosis and treatment and the condition of the child during the diagnosis and treatment process; Determine auxiliary diagnosis and treatment methods based on the condition of the child and the difficulty of diagnosis and treatment.

[0030] Optionally, the external diaphragm pacing diagnosis and treatment effect evaluation system further includes a frequency and concentration determination module, which is used to: Determine the degree of compliance with instructions based on the age of the child; Determine the difficulty of inducing cough based on the child's condition; determining cough assistance means according to the degree of compliance with the instruction and the difficulty of inducing the cough; Based on the age and medical information of the child, the cough stimulation frequency and the concentration of the cough irritant in the cough assistive means are determined.

[0031] Optionally, the level determination module is used to match the weights of the child's age, the basic lung function index, the BPD severity grade, and the number of comorbidities on the condition of the BPD child based on the BPD onset information: According to the monthly age distribution data, matching the weight of the impact of the child's age on the condition of the BPD child; Analyzing the physiological data to determine the real-time fluctuation amplitude of the blood oxygen saturation of the BPD child; According to the real-time fluctuation amplitude and the BPD onset information, the weights of the basic lung function index and the number of comorbidities affecting the condition of the BPD child are matched; According to the age of the child, the real-time fluctuation amplitude and the BPD onset information, the BPD severity grade is matched with the weight of the condition of the BPD child. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application; Figure 2 This is a flow chart of a method for evaluating the diagnostic and therapeutic effects of external diaphragm pacing provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of an external diaphragm pacing diagnosis and treatment effect evaluation system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0034] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0035] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0036] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0037] Children with BPD suffer from structural lesions such as long-term atelectasis and bullae, which lead to a flat diaphragm, disuse atrophy, and sputum discharge dysfunction, forming a vicious cycle of "decreased diaphragmatic function-exacerbated respiratory failure." In theory, EDP can break this cycle by enhancing the efficiency of diaphragmatic contraction and improving cough motivation. However, existing evaluation methods often use unified standards and focus on a single or a few macro-indicators for evaluation, resulting in poor universality of evaluation results and limited reference value, which restricts the precise application of EDP technology in the treatment of children with BDP and the optimization of efficacy.

[0038] Based on this, the present application provides a method and system for evaluating the diagnostic and treatment effects of external diaphragm pacing, which obtains the diagnostic and treatment information of BPD children and their physiological data before and after EDP treatment, avoids evaluation bias caused by missing or inconsistent data, and improves the repeatability and quantification of the evaluation. According to the diagnostic and treatment information, the individual functional level of the BPD child is determined, and the evaluation bias caused by ignoring individual factors is eliminated, so that the evaluation results more truly reflect the overall physiological state of the child. According to the physiological data and individual functional level, the changes in respiratory muscle function, diaphragm function and expectoration ability of the BPD child are determined to reflect the improvement of respiratory muscle strength, avoid the one-sidedness of subjective clinical observation, capture the overall impact of EDP on diaphragm function, and correlate the cough-inducing effect of EDP to avoid one-sidedness of the evaluation. Based on the changes in respiratory muscle function, diaphragm function and expectoration ability, the diagnostic and treatment effects of EDP are comprehensively evaluated to eliminate the defects of lack of multi-dimensional integration mechanism and inability to provide quantifiable results.

[0039] Figure 1 This is a schematic diagram of an application scenario provided by this application. The method provided by this application is applied when evaluating the diagnostic and therapeutic effects of external diaphragm pacing.

[0040] Specifically, the method provided in the present application is applied to any server, and the server interacts with the hospital information management system, and obtains the diagnosis and treatment information of BPD children and the physiological data before and after receiving EDP diagnosis and treatment through the hospital information management system. According to the diagnosis and treatment information, the individual functional level of the BPD child is determined. According to the physiological data and the individual functional level, the changes in the respiratory muscle function, diaphragm function and expectoration ability of the BPD child are determined to reflect the improvement of respiratory muscle strength, avoid the one-sidedness of subjective clinical observation, capture the overall impact of EDP on diaphragm function, and associate the cough-inducing effect of EDP to avoid one-sidedness in the evaluation. Based on the changes in respiratory muscle function, diaphragm function and expectoration ability, the diagnosis and treatment effect of EDP is comprehensively evaluated to eliminate the defects of lack of multi-dimensional integration mechanism and inability to provide quantifiable results. For specific implementation methods, please refer to the following embodiments.

[0041] Figure 2 This is a flow chart of a method and system for evaluating the effect of external diaphragm pacing diagnosis and treatment provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201. Obtain diagnosis and treatment information of children with BPD and physiological data before and after receiving EDP diagnosis and treatment; Babies with BPD may be premature infants with bronchopulmonary dysplasia.

[0042] Diagnostic and treatment information can be basic medical data of BPD children extracted from clinical records, including the child's age, BPD severity grade, number of comorbidities, and basic lung function indicators, which are stored in the hospital information management system, which can be updated dynamically in real time.

[0043] The period before and after EDP diagnosis and treatment can be the period before and after the start of external diaphragmatic pacing treatment.

[0044] The physiological data may be physiological index data, including index data such as respiratory muscle function-related data, diaphragm function-related data, and expectoration ability-related data, which are stored in a hospital information management system.

[0045] Specifically, the age of the child, BPD severity grade (bronchopulmonary dysplasia is graded based on clinical criteria, such as mild, moderate, or severe), number of comorbidities (the number of other diseases that BPD children have at the same time, such as heart disease or infection diagnosis), and basic lung function indicators (quantitative parameters reflecting the basic status of the lungs, such as vital capacity, etc.) were retrieved from the hospital information management system to determine the diagnosis and treatment information of the BPD child.

[0046] Respiratory muscle function-related data recorded before and after the EDP treatment (respiratory muscle strength indicators measured by a spirometer, including maximum inspiratory pressure (MIP) and maximum expiratory pressure (MEP)), diaphragm function-related data (diaphragm status parameters measured by ultrasound or imaging equipment, such as diaphragm thickness (muscle layer thickness when the diaphragm contracts under ultrasound measurement) and diaphragm movement amplitude (the up and down movement distance of the diaphragm during the respiratory cycle recorded by imaging equipment)), and sputum discharge ability-related data (indicators of sputum discharge efficiency measured by a flow meter, in which sputum discharge volume is collected for a fixed period of time and recorded by weighing, such as peak cough flow rate (the highest flow rate of airflow through the respiratory tract when coughing hard)) were retrieved from the hospital information management system to determine the physiological data before and after the EDP treatment; among them, the physiological data before the EDP treatment were collected before the start of treatment, and the physiological data after the EDP treatment were collected after the end of treatment.

[0047] S202. Determine the individual functional level of the child with BPD based on the diagnosis and treatment information; Individual functional level can be a comprehensive indicator of the overall physiological status of children with BPD.

[0048] Specifically, the child's age is extracted based on the diagnosis and treatment information; then, the same-age group in the hospital information management system is queried (the group of BPD children in the hospital information management system who are the same age as the target child (e.g., within ±2 weeks)), and the z-score value of the child's age relative to the same-age group is calculated (the standard deviation offset between the child's age and the mean age of the same-age group).

[0049] In a specific implementation, a pre-set BPD severity classification can be established based on historical diagnosis and treatment information stored in the hospital information management system.

[0050] The pre-set BPD severity grade and number of comorbidities were extracted, and the weight coefficient preset through clinical data (BPD children's diagnosis and treatment records) was applied to calculate the current child's symptom score, and the BPD severity level was divided according to the score. For example, a severe grade in the BPD severity grade indicates worse lung function, so it is given a negative weight, and the score is linearly reduced as the number of comorbidities increases.

[0051] The above data were integrated and the age z-score value and symptom score were weighted and summed to determine the individual functional level.

[0052] S203. Determine changes in respiratory muscle function, diaphragmatic function, and expectoration ability in children with BPD based on physiological data and individual functional levels; The change in respiratory muscle function may be the amount of change in respiratory muscle strength.

[0053] The change in diaphragm function may be a change in the state of the diaphragm.

[0054] The change in expectoration ability may be a change in expectoration efficiency.

[0055] Specifically, the physiological data is analyzed to determine the maximum inspiratory pressure and maximum expiratory pressure in the physiological data, and the difference between the EDP value after diagnosis and treatment and the EDP value before diagnosis and treatment (i.e., the absolute change) is calculated; then, the individual functional level is applied to perform noise correction: the individual functional level is used as a correction factor to normalize the difference (for example, when the individual functional level is low, the change value is amplified to eliminate the influence of basic fluctuations), thereby determining the changes in respiratory muscle function.

[0056] The average change rate of the diaphragm thickness and diaphragm movement amplitude in the physiological data was calculated using the average value algorithm; then, combined with the diaphragm expectoration coordination level (the correlation between diaphragm contraction (quantification of diaphragm movement amplitude) and expectoration efficiency (the ability to clear sputum per unit time), obtained by analyzing the correlation between cough peak flow rate and sputum output in the physiological data), changes in diaphragm function were determined.

[0057] Based on the peak cough flow rate and sputum output in the physiological data, the difference between the EDP post-treatment value and the EDP pre-treatment value is calculated; then, the change in diaphragm function is used for correction (the change in diaphragm function is used as a correction factor for the basic change rate (for example, when the change in diaphragm function is significant, the change in sputum discharge ability is magnified)) to determine the change in sputum discharge ability (such as the improvement rate of sputum discharge efficiency).

[0058] S204. Comprehensively evaluate the effectiveness of EDP diagnosis and treatment based on changes in respiratory muscle function, diaphragmatic function, and expectoration capacity.

[0059] The EDP diagnosis and treatment effect can be the result of a comprehensive evaluation of the EDP diagnosis and treatment effect.

[0060] Specifically, the changes in respiratory muscle function, diaphragmatic function, and expectoration ability are weighted using preset weights (the weight coefficient is calculated in real time based on the child's age or basic lung function indicators); then, the weighted changes in respiratory muscle function, diaphragmatic function, and expectoration ability are summed to comprehensively evaluate the EDP diagnosis and treatment effect.

[0061] Through this program, the diagnosis and treatment information of children with BPD and their physiological data before and after EDP diagnosis and treatment are obtained, avoiding assessment bias caused by missing or inconsistent data and improving the repeatability and quantification of the assessment. Based on the diagnosis and treatment information, the individual functional level of children with BPD is determined, eliminating the assessment bias caused by ignoring individual factors, so that the assessment results more truly reflect the overall physiological status of the children. Based on physiological data and individual functional levels, the changes in respiratory muscle function, diaphragm function and expectoration ability of children with BPD are determined to reflect the improvement of respiratory muscle strength, avoid the one-sidedness of subjective clinical observations, capture the overall impact of EDP on diaphragm function, and correlate the cough-inducing effect of EDP to avoid one-sidedness of the assessment. Based on the changes in respiratory muscle function, diaphragm function and expectoration ability, the diagnosis and treatment effects of EDP are comprehensively evaluated to eliminate the defects of lacking a multi-dimensional integration mechanism and being unable to provide quantifiable results.

[0062] In some embodiments, the diagnosis and treatment information is analyzed to determine the child's age, BPD severity grade, number of comorbidities, and basic lung function indicators; BPD onset information is obtained; based on the BPD onset information, the child's age, basic lung function indicators, BPD severity grade, and number of comorbidities are matched with the weights of the BPD child's condition; based on the BPD onset information, the child's age and basic lung function indicators are converted into positive z-score values; the BPD severity grade and the number of comorbidities are converted into negative z-score values; and based on the condition impact weights, positive z-score values, and negative z-score values, the individual functional level of the BPD child is calculated and determined.

[0063] The child's age can be the numerical age of the child with BPD.

[0064] The BPD severity classification can be a severity level value of the disease in children with BPD, which is divided into mild, moderate, and severe.

[0065] The number of comorbidities can be the number of related diseases that children with BPD have.

[0066] Basic lung function indicators can indicate the lung function status of children with BPD.

[0067] BPD incidence information can be a historical population incidence data set, including the age, basic lung function indicators, BPD severity grade, number of comorbidities, and recurrence rate of respiratory failure within 6 months after discharge of multiple historical BPD children.

[0068] The disease impact weight can be a numerical weight calculated through multivariate regression analysis, which corresponds to the relative impact of the child's age, basic lung function indicators, BPD severity grade, and number of comorbidities.

[0069] The positive z-score value can be a standardized score representing a positively correlated parameter (child's age or basic lung function index).

[0070] Negative z-score values ​​can be standardized scores that represent negative correlation parameters (BPD severity grade or number of comorbidities).

[0071] Specifically, the diagnosis and treatment information is parsed to obtain the child's age in months (for example, the current age in months is calculated from the date of birth); then, the BPD severity grade is determined based on the standard clinical grade (used to quantify the severity of BPD in children) established according to the clinical assessment data in the diagnosis and treatment information (for example, mild is grade 1, moderate is grade 2, and severe is grade 3); the number of comorbidities in the diagnosis and treatment information is counted (for example, entries for heart disease, infection, and other diseases); and the measurement values ​​of vital capacity or oxygenation index (a quantitative parameter indicating the oxygenation efficiency of the lungs) are extracted from the diagnosis and treatment information as basic lung function indicators.

[0072] A preset historical database is constructed by collecting diagnosis and treatment data of a historical group of children with BPD (a collection of children diagnosed with BPD in the past, used to construct BPD incidence information, generally stored in a database and called up when used). BPD incidence information (which stores historical BPD child group data, including child age, baseline lung function indicators, BPD severity grade, number of comorbidities, and the recurrence rate of respiratory failure within 6 months after discharge of historical BPD children) is obtained from the preset historical database.

[0073] Based on the BPD incidence information, a multivariate regression analysis was performed. The dependent variable was set as the recurrence rate of respiratory failure within 6 months after discharge from the historical data. The independent variables were set as the age, baseline lung function indicators, BPD severity grade, and number of comorbidities of the historical BPD children. A linear regression model was used to calculate the regression coefficient of each independent variable. The calculated regression coefficient was directly applied to the BPD children as their corresponding disease impact weight.

[0074] The mean and standard deviation of the children's age were obtained from the BPD onset information; the z-score was calculated based on the mean and standard deviation as the positive z-score value (a larger value indicates a more favorable condition for the child); the mean and standard deviation of the baseline pulmonary function indicators were obtained from the BPD onset information; the z-score was calculated based on the mean and standard deviation as the positive z-score value (a larger value indicates a more favorable condition for the child).

[0075] The mean and standard deviation of BPD severity grades were obtained from BPD onset information. A z-score was calculated based on the mean and standard deviation, which was used as a negative z-score value (a higher value indicates a less favorable outcome for the child). The number of comorbidities was also obtained from BPD onset information. A z-score was calculated based on the mean and standard deviation, which was used as a negative z-score value (a higher value indicates a less favorable outcome for the child). The individual functioning level of the BPD child was then calculated by combining the disease impact weight with the z-score value.

[0076] Through this solution, diagnosis and treatment information is parsed to determine the child's age, BPD severity grade, number of comorbidities, and baseline lung function indicators, generating a structured, numerical parameter set to ensure direct operation and avoid missing or ambiguous parameters. BPD incidence information is obtained to ensure the reliability and adaptability of the assessment. Based on BPD incidence information, the weights of the child's age, baseline lung function indicators, BPD severity grade, and number of comorbidities on the BPD child's condition are matched, and standardized weights are generated for weighted calculations to ensure that individual factors are accurately weighted in the assessment. Based on BPD incidence information, the child's age and baseline lung function indicators are converted into positive z-score values, making different parameters such as the child's age and baseline lung function indicators comparable and strengthening the contribution direction of the positive parameters. The z-score eliminates dimensional differences, and the positive conversion ensures parameter direction consistency. The higher the values ​​of the child's age and baseline lung function indicators, the more favorable it is. The BPD severity grade and number of comorbidities were converted to negative z-score values, making them comparable and emphasizing the contribution of negative parameters. The z-score eliminates dimensional differences, and the negative conversion ensures directional consistency. Higher values ​​for BPD severity grade and number of comorbidities are associated with a more unfavorable outcome. The individual functional level of children with BPD was calculated based on the disease impact weight, positive z-score values, and negative z-score values. This was used to analyze the effectiveness of EDP diagnosis and treatment, ensuring that the results reflect the individualized comprehensive status.

[0077] In some embodiments, based on the BPD onset information, the mean age and standard deviation of BPD onset are determined; based on the mean age and standard deviation of BPD onset, the conversion of the positive z-score value corresponding to the child's age is determined; based on the BPD onset information, the mean lung function index and standard deviation of lung function of children in the same period are determined; based on the mean lung function index and standard deviation of lung function, the conversion of the positive z-score value corresponding to the basic lung function index is determined.

[0078] The mean age of BPD onset may be the mean age of onset during the same period extracted from BPD onset information.

[0079] The age standard deviation can be the age standard deviation of onset during the same period extracted from the BPD onset information.

[0080] Children of the same period can be the group of children belonging to the same historical period in the BPD onset information.

[0081] The mean value of the pulmonary function index may be the arithmetic mean value of the basic pulmonary function index values ​​of the onset of the same period extracted from the BPD onset information.

[0082] The standard deviation of lung function may be the standard deviation of the basic lung function index values ​​of the same period of onset extracted from the BPD onset information.

[0083] Specifically, based on the BPD onset information, the age values ​​of all historical children were extracted; the arithmetic mean of the age values ​​was calculated to obtain the mean age of BPD onset; at the same time, the standard deviation of the age values ​​was calculated to obtain the age standard deviation.

[0084] Based on the mean age and standard deviation of BPD onset age, the conversion of the positive z-score value corresponding to the child's age was determined using the following formula: (1); in, Indicates the positive z-score value corresponding to the child's age; Indicates the age of the child; represents the mean age of onset of BPD; represents the standard deviation of age.

[0085] In formula (1), the patient's age is calculated The mean age of onset of BPD Then, by subtracting , eliminate the interference of individual age, divide the difference by the age standard deviation ,get ;according to Scaling to adapt the results to different population variations: If Small (concentrated age distribution), Amplify the impact of deviation and highlight the risk of disease in young children; if Large (dispersed age distribution), Reduce the impact of deviation and avoid misjudgment.

[0086] Based on the BPD incidence information, the basic lung function index values ​​of all historical children were extracted, and the arithmetic mean of the basic lung function index values ​​was calculated to obtain the mean lung function index; at the same time, the standard deviation of the basic lung function index values ​​was calculated to obtain the standard deviation of lung function.

[0087] According to the mean and standard deviation of lung function indicators, the conversion of the positive z-score value corresponding to the basic lung function indicators is determined using the following formula: (2); in, Indicates the positive z-score value corresponding to the basic lung function index; Indicates the age of the child; represents the mean value of lung function index; represents the standard deviation of lung function.

[0088] In formula (2), the basic lung function index is calculated and lung function index mean Then, divide the difference by the standard deviation of lung function ,get ;pass Scaling to adapt the results to different population variations: If Small (centralized distribution of lung function), Amplify the impact of deviations and highlight the risk of illness in children with low lung function; if Large (lung function is dispersed), Minimize the impact of deviations and avoid over-interpreting small deviations.

[0089] Through this solution, based on BPD onset information, the mean age and standard deviation of BPD onset are determined, eliminating assessment bias caused by age developmental differences and ensuring that the age values ​​of children of different months can be fairly compared. Based on the mean age and standard deviation of BPD onset, the conversion of positive z-score values ​​corresponding to the child's age is determined to eliminate the problem of incomparable absolute respiratory function values ​​in children of different months. Based on BPD onset information, the mean and standard deviation of lung function indicators for children of the same period are determined to eliminate the reliance on the absolute values ​​of individual indicators in the assessment. Based on the mean and standard deviation of lung function indicators, the conversion of positive z-score values ​​corresponding to basic lung function indicators is determined to make the lung function values ​​of children of different ages comparable. At the same time, the weights are optimized for EDP treatment needs to improve analysis accuracy.

[0090] In some embodiments, physiological data are analyzed to determine the maximum inspiratory pressure and maximum expiratory pressure before and after treatment; the rate of change of respiratory muscle strength before and after treatment is determined based on the maximum inspiratory pressure and maximum expiratory pressure before and after treatment; the rate of change of respiratory muscle strength is corrected based on the individual functional level, and the change in respiratory muscle function of children with BPD is determined; physiological data are analyzed to determine the diaphragm thickness and diaphragm movement amplitude before and after treatment; the rate of change of diaphragm thickness and diaphragm movement before and after treatment are determined based on the diaphragm thickness and diaphragm movement amplitude before and after treatment; the change in diaphragm function of children with BPD is determined based on the rate of change of diaphragm thickness and diaphragm movement before and after treatment; physiological data are analyzed to determine the peak cough flow rate before and after treatment and the amount of sputum discharged in a preset time period before and after treatment; the basic rate of change of sputum discharge is determined based on the peak cough flow rate before and after treatment and the amount of sputum discharged in a preset time period.

[0091] Before and after treatment can be two time points before the start of EDP treatment and after the end of treatment.

[0092] Maximal inspiratory pressure may be the peak pressure value measured during maximal inspiratory effort and may be expressed in centimeters of water column, representing inspiratory muscle strength.

[0093] Maximum expiratory pressure may be the peak pressure value measured during maximal expiratory effort and may be expressed in centimeters of water column, representing expiratory muscle strength.

[0094] The rate of change of respiratory muscle strength can be a percentage change value calculated based on the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment.

[0095] The diaphragm thickness may be a diaphragm tissue thickness value.

[0096] The diaphragm movement amplitude can be the maximum displacement value during the respiratory cycle.

[0097] The diaphragm thickness change rate may be a percentage change value calculated based on the diaphragm thickness before and after diagnosis and treatment.

[0098] The diaphragm movement change rate may be a percentage change value calculated based on the diaphragm movement amplitude before and after diagnosis and treatment.

[0099] The peak cough flow rate may be the maximum airflow velocity value measured during coughing, which may be expressed in L / min and represents coughing capacity.

[0100] The preset time period may be a preset time interval, which is pre-stored in the server and called when used.

[0101] The sputum output can be the volume or weight of sputum collected within a preset period of time.

[0102] The basal change rate of sputum discharge can be a comprehensive percentage change value calculated based on the peak cough flow rate and sputum discharge volume before and after diagnosis and treatment.

[0103] Specifically, the physiological data were analyzed. Before the start of EDP diagnosis and treatment, the maximum inspiratory pressure and maximum expiratory pressure of BPD children were recorded using a spirometer (BPD children performed maximum inspiratory and expiratory efforts in a quiet state); at the same time, after the end of EDP diagnosis and treatment, the maximum inspiratory pressure and maximum expiratory pressure values ​​of BPD children were recorded using a spirometer.

[0104] The rate of change in respiratory muscle strength before and after treatment was calculated as a percentage based on the maximum inspiratory and expiratory pressures before and after diagnosis and treatment. The individual functional level weighting factor was determined based on the individual functional level; the rate of change in respiratory muscle strength was corrected using the individual functional level weighting factor (for example, if the individual functional level was high (indicating good overall condition), the individual functional level weighting factor was set; if the individual functional level was low, the individual functional level weighting factor was set to adjust the rate of change in respiratory muscle strength downward). The rate of change in respiratory muscle strength of the combined maximum inspiratory and maximum expiratory pressures was averaged as the final change in respiratory muscle function.

[0105] Physiological data were analyzed. Before the start of EDP diagnosis and treatment, ultrasound equipment was used to measure the diaphragm thickness and diaphragm movement amplitude of BPD children. At the same time, ultrasound equipment was used to measure the diaphragm thickness and diaphragm movement amplitude of BPD children after the end of EDP diagnosis and treatment.

[0106] The diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment were used to calculate the diaphragm thickness change rate and diaphragm movement change rate by percentage.

[0107] The average of the rate of change in diaphragmatic thickness and the rate of change in diaphragmatic movement was calculated and used as the change in diaphragmatic function in children with BPD. Physiological data were analyzed to identify pre-EDP diagnosis and treatment items and extract peak cough flow rate and sputum output within a preset time period (e.g., 30 minutes). Post-EDP diagnosis and treatment items were also identified and extracted peak cough flow rate and sputum output within a preset time period (e.g., 30 minutes).

[0108] Based on the peak cough flow rate before and after diagnosis and treatment and the sputum discharge volume within the preset time period, the basic sputum discharge change rate is determined by the change rate calculation formula established using the standard relative change calculation principle.

[0109] Through this program, physiological data is analyzed to determine the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment, eliminating the problem of difficulty in quantifying changes in respiratory muscle function. Based on the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment, the rate of change of respiratory muscle strength before and after diagnosis and treatment is determined, and the difference in respiratory muscle strength is converted into a comparable standardized indicator, eliminating the problem of high noise in the data of changes in respiratory muscle function. According to the individual functional level, the rate of change of respiratory muscle strength is corrected to determine the changes in respiratory muscle function of children with BPD, eliminating the problem of lack of personalized assessment mechanism and ensuring that the change value of respiratory muscle function truly reflects the specific effect of EDP. Physiological data is analyzed to determine the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, eliminating the problem of difficulty in quantifying changes in diaphragm function and avoiding the one-sidedness of relying on imaging observations. Based on the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, the rate of change of diaphragm thickness and diaphragm movement before and after diagnosis and treatment are determined, eliminating the problem of not being able to capture the overall impact of EDP on diaphragm function. Based on the rate of change in diaphragm thickness and diaphragm movement before and after diagnosis and treatment, changes in diaphragm function in children with BPD are determined, eliminating the lack of a comprehensive assessment of diaphragm function changes and avoiding the inadequacy of focusing on a single parameter. Analyze physiological data to determine the peak cough flow rate before and after diagnosis and treatment, as well as the amount of sputum discharged during the preset time period before and after diagnosis and treatment, ensuring that the data can serve the calculation of the rate of change and avoiding the one-sidedness of relying on simple records. Based on the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged during the preset time period, the basic rate of change in sputum discharge is determined, providing a complete quantitative value of the change in sputum discharge ability for the EDP diagnosis and treatment effect.

[0110] In some embodiments, changes in diaphragmatic function are analyzed to determine the diaphragmatic sputum elimination coordination level; the sputum elimination basic change rate is determined based on the diaphragmatic sputum elimination coordination level, the peak cough flow rate before and after diagnosis and treatment, and the sputum discharge volume within a preset time period.

[0111] The diaphragmatic synergy level of expectoration can be a quantitative correlation between the diaphragmatic contraction function and expectoration efficiency.

[0112] Specifically, the changes in diaphragm function are analyzed. Changes in diaphragm function reflect the improvement or deterioration of the overall functional state of the diaphragm. When the diaphragm function improves (such as increased diaphragm thickness and increased movement amplitude), the diaphragm contraction force is enhanced, which directly improves the airflow generation ability and sputum propulsion efficiency during coughing; in EDP diagnosis and treatment, the regular contraction of the diaphragm (achieved by stimulating the phrenic nerve through electrodes) can effectively induce a cough reflex, thereby increasing the peak cough flow rate and sputum discharge volume; conversely, deterioration of diaphragm function will weaken the cough ability, resulting in reduced sputum discharge efficiency.

[0113] Then, according to the changes in diaphragm function and the impact of the above-mentioned changes in diaphragm function on expectoration, the diaphragm expectoration coordination level is mapped through preset association rules. For example, when the diaphragm function change is positive (indicating improvement), the diaphragm expectoration coordination level is high, and the corresponding auxiliary expectoration efficiency is improved (such as increased cough peak flow rate and increased sputum discharge volume), and the corresponding auxiliary expectoration degree can reach a significant level; if the diaphragm function change is negative (indicating deterioration), the diaphragm expectoration coordination level is low, the corresponding auxiliary expectoration efficiency is reduced, and the corresponding auxiliary expectoration degree is proportional to the diaphragm function change.

[0114] Based on the peak cough flow rate before and after diagnosis and treatment, the standard percentage change formula is used to calculate the change rate of peak cough flow rate; based on the sputum discharge volume within the preset time period, the standard percentage change formula is used to calculate the change rate of sputum discharge volume; the average of the change rate of peak cough flow rate and the change rate of sputum discharge volume is taken as the preliminary sputum discharge change rate.

[0115] The initial expectoration change rate is corrected using the diaphragmatic expectoration synergy level. When the diaphragmatic expectoration synergy level is positive (indicating improved diaphragmatic function), the initial expectoration change rate is adjusted upward (enhanced basal expectoration change rate). When the diaphragmatic expectoration synergy level is negative (indicating worsening diaphragmatic function), the initial expectoration change rate is adjusted downward (weakened basal expectoration change rate), thereby determining the final basal expectoration change rate.

[0116] This protocol analyzes changes in diaphragmatic function and determines the level of diaphragmatic synergy in expectoration, avoiding subjective assessments and making the quantitative basis for expectoration efficiency more reliable and repeatable. The baseline rate of change in expectoration is determined based on the level of diaphragmatic synergy in expectoration, peak cough velocity before and after diagnosis and treatment, and sputum output within a preset time period. This not only reflects direct changes in coughing and sputum output but also captures the diaphragm's synergistic effect on expectoration, achieving comprehensive quantification of expectoration efficiency and providing repeatable evaluation results for EDP diagnosis and treatment effectiveness.

[0117] In some embodiments, BPD incidence information is analyzed to determine the monthly age distribution data of the diseased group; the monthly age distribution data and the age of the children are analyzed to determine the skewness of the monthly age distribution; based on the skewness of the monthly age distribution, the weight of the impact of the child's age on the condition of the BPD child is determined; BPD incidence information is analyzed to determine the median lung function of children in the same period; the functional benchmark value of healthy lung function is obtained; based on the median lung function and functional benchmark value of children in the same period, the weight of the impact of basic lung function indicators on the condition of the BPD child is determined.

[0118] The patient population may be a population of children with bronchopulmonary dysplasia (BPD).

[0119] The monthly age distribution data can be the frequency statistics results of the monthly age of a group of children with BPD.

[0120] The skewness of the monthly age distribution can be a quantitative value of the degree of asymmetry of the monthly age distribution data.

[0121] The median lung function of children in the same period can be the median value of the basic lung function indicators of the BPD children group.

[0122] Healthy lung function can be the standard reference data of lung function in a healthy child group.

[0123] The functional benchmark value can be the standard value of the lung function index of healthy children of the same age.

[0124] Specifically, BPD onset information was analyzed, and the monthly age entries for the affected group were identified and summarized to determine the monthly age distribution data for the affected group. Based on the monthly age distribution data, standard statistical methods were applied to analyze the distribution shape to determine whether it was left- or right-skewed. Furthermore, the patient's age was compared with the monthly age distribution data to quantify their relative position (the statistical position of the currently assessed child's age within the monthly age distribution data set for the affected group, which was used to determine the skewness of the monthly age distribution) and determine the skewness of the monthly age distribution.

[0125] Based on clinical experience, a preset mapping table was established (storing the correspondence between skewness range and weight, which is used to directly convert the skewness of the monthly age distribution into the weight of the impact of the child's age on the condition). The skewness of the monthly age distribution was converted into the weight of the impact of the child's age on the condition of BPD children through the preset mapping table.

[0126] BPD onset information was parsed, and data entries for children from the same period were screened (based on the timestamp field) to extract baseline pulmonary function indicators. The median of baseline pulmonary function indicators, i.e., the median pulmonary function of children from the same period, was calculated using a standard median algorithm. The Pediatric Physiological Reference Database (which stores standard pulmonary function values ​​for healthy children at different months of age and serves as a baseline for healthy controls) was accessed based on the child's age to extract the baseline value for healthy pulmonary function corresponding to the child's age.

[0127] The median lung function of children in the same period was compared with the functional baseline value; the comparison results were mapped to weight values ​​through a preset weight conversion table (which stores the correspondence between the deviation rate range and the functional baseline value of children in the same period and the weight value, and is used to map the comparison results to the disease impact weight of the basic lung function indicators), thereby determining the disease impact weight of the basic lung function indicators on the children with BPD.

[0128] Through this solution, BPD incidence information is analyzed and the monthly age distribution data of the diseased group is determined. The monthly age distribution data and the age of the children are analyzed to determine the skewness of the monthly age distribution, ensuring that the group age distribution pattern is accurately captured to reflect the trend of the impact of the group distribution on the individual condition. Based on the skewness of the monthly age distribution, the weight of the impact of the child's age on the condition of BPD children is determined, and directly used for the overall calculation of the EDP diagnosis and treatment effect. The BPD incidence information is analyzed to determine the median lung function of children in the same period, ensuring that the weight of the basic lung function indicators is determined based on group data. The functional baseline value of healthy lung function is obtained to enhance the objectivity of the assessment. Based on the median lung function and functional baseline value of children in the same period, the weight of the impact of the basic lung function indicators on the condition of BPD children is determined, which is used for the overall calculation of the EDP diagnosis and treatment effect, realizing the parallel matching of the two weights.

[0129] In some embodiments, the diagnostic and treatment equipment is determined based on the age of the child; the difficulty of diagnosis and treatment and the condition of the child during the treatment process are analyzed and determined based on the age of the child; and auxiliary diagnostic and treatment methods are determined based on the condition of the child and the difficulty of diagnosis and treatment.

[0130] The diagnostic and treatment device can be the physical device used for EDP treatment, including the size of the electrode pads (such as small, medium or large).

[0131] Diagnostic difficulty can be the degree of challenge in the treatment process of EDP.

[0132] The child's status can be the degree of behavioral cooperation of the child during the EDP diagnosis and treatment process.

[0133] Auxiliary diagnostic and therapeutic methods can be auxiliary measures used in the treatment of EDP.

[0134] Specifically, according to the age of the child, the preset device mapping table constructed through clinical experience is retrieved (storing the mapping relationship between the age range of the child and the corresponding electrode size, for example, the age range is defined as 0-6 months corresponding to small electrode, 6-12 months corresponding to medium electrode, and 12 months and above corresponding to large electrode), the age range of the child in the preset device mapping table is matched, and the corresponding electrode size is determined as the diagnostic and treatment equipment.

[0135] The patients are divided into age categories based on their age (for example, those under 6 months are newborns, those between 6 and 12 months are infants, and those over 12 months are toddlers). Preset difficulty levels are mapped based on age categories (a mapping relationship between age categories and diagnosis and treatment difficulty is stored, used to identify treatment challenges (such as high difficulty for young patients) to reduce the risk of EDP interruption), and the diagnosis and treatment difficulty is determined. For example, newborns correspond to high difficulty, infants correspond to medium difficulty, and toddlers correspond to low difficulty. The patient's age is determined by pre-set status analysis rules constructed through clinical experience (a mapping relationship between the patient's age range and the corresponding degree of compliance with instructions is stored, used to generate the patient's status based on the patient's age. For example, if the child is under 6 months old, the child's status is low compliance with instructions, and if the child is over 6 months old, the child's status is medium compliance with instructions).

[0136] According to the child's condition and the difficulty of diagnosis and treatment, the preset auxiliary means mapping table constructed through clinical rules is queried (the mapping relationship between the combination of instruction cooperation and diagnosis and treatment difficulty and the corresponding auxiliary diagnosis and treatment means is stored. For example, when the child's condition is poor and the diagnosis and treatment difficulty is high, the position adjustment (changing the child's posture) and the use of sedatives (used to stabilize the child's mood and position) are determined; when the child's condition is medium and the diagnosis and treatment difficulty is medium, the cough stimulation frequency optimization (adjusting EDP (such as stimulation frequency) to enhance cough reflex) is determined to improve cough induction), and the corresponding auxiliary diagnosis and treatment means (such as position adjustment, sedative use or cough stimulation frequency optimization) are determined.

[0137] This solution determines the diagnostic and treatment equipment based on the patient's age, improving the accuracy and safety of EDP stimulation and avoiding invalid data due to device mismatch. Based on the patient's age, the difficulty of diagnosis and treatment and the patient's condition during treatment are analyzed and determined to reduce unexpected events during EDP treatment and prevent data loss due to poor compliance. Auxiliary diagnostic and treatment methods are determined based on the patient's condition and the difficulty of diagnosis and treatment to avoid data bias caused by the patient's agitation.

[0138] In some embodiments, the degree of compliance with instructions is determined based on the age of the child; the difficulty of inducing a cough is determined based on the condition of the child; a cough assistance method is determined based on the degree of compliance with instructions and the difficulty of inducing a cough; and the cough stimulation frequency and cough irritant concentration in the cough assistance method are determined based on the age and medical information of the child.

[0139] Compliance can be defined as the child's ability to respond to EDP treatment instructions.

[0140] Cough induction difficulty may be the degree of challenge in inducing a cough reflex during EDP treatment.

[0141] Cough assistive measures may include postural adjustments, the use of sedatives, or optimization of the frequency of cough stimulation.

[0142] The cough stimulation frequency may be the stimulation frequency set in the EDP treatment.

[0143] The cough irritant concentration may be the irritant concentration used in EDP treatment.

[0144] Specifically, the children are divided into age categories according to their age; the compliance with instructions (the child's ability to respond to treatment instructions, such as the compliance with instructions of newborns and infants is defined as poor, and the compliance with instructions of toddlers is defined as moderate) is inferred based on the age categories; then, the compliance with instructions is used as the child's status.

[0145] The degree of compliance with instructions is directly converted into the child's condition; the difficulty of inducing cough is determined according to the child's condition. For example, when the child's condition is poor, the difficulty of inducing cough is defined as high; when the child's condition is medium, the difficulty of inducing cough is defined as medium.

[0146] According to the command compliance and cough induction difficulty, the preset auxiliary means mapping table is queried to determine the cough auxiliary means. For example, when the command compliance is poor and the cough induction difficulty is high, the cough auxiliary means are determined to be position adjustment and sedative use; when the command compliance is medium and the cough induction difficulty is medium, the cough auxiliary means are determined to be cough stimulation frequency optimization.

[0147] According to the child's age and medical information, access the preset stimulation frequency mapping table (storing the mapping relationship between the child's age range and medical information and the cough stimulation frequency value, which is used to match the cough stimulation frequency according to the child's age and medical information. For example, when the child is younger than 6 months and the severity of BPD is high, the cough stimulation frequency is higher; when the child is older than 12 months and the severity of BPD is low, the cough stimulation frequency is lower) to determine the cough stimulation frequency in the cough assistive means.

[0148] Based on the patient's age and medical information, access the preset irritant concentration mapping table (which stores a mapping between the patient's age range and medical information and cough irritant concentration values, used to set cough irritant concentrations based on the patient's age and medical information). For example, if the patient is under 6 months old, the cough irritant concentration is set to 5%; if the child is over 12 months old, the cough irritant concentration is set to 2%. Determine the cough irritant concentration for the cough assist method.

[0149] Through this program, the degree of compliance with instructions is determined according to the age of the child, and the selection of personalized auxiliary means is guided to avoid incomplete data collection due to the child's non-cooperation. According to the child's condition, the difficulty of cough induction is determined, the cough induction process is optimized, and the effectiveness of EDP treatment is ensured. According to the degree of compliance with instructions and the difficulty of cough induction, cough auxiliary means are determined to enhance the induction effect of cough reflex, thereby improving the integrity and reliability of physiological data collection. Based on the child's age and diagnosis and treatment information, the cough stimulation frequency and cough irritant concentration in the cough auxiliary means are determined to achieve refined setting of EDP parameters, optimize cough induction intensity, ensure personalized treatment process, and thus improve the accuracy and repeatability of data collection.

[0150] In some embodiments, based on the monthly age distribution data, the weight of the impact of the child's age on the BPD child's condition is matched; the physiological data is analyzed to determine the real-time fluctuation amplitude of the blood oxygen saturation of the BPD child; based on the real-time fluctuation amplitude and BPD onset information, the weight of the impact of basic lung function indicators and the number of comorbidities on the BPD child's condition is matched; based on the child's age, real-time fluctuation amplitude and BPD onset information, the weight of the impact of BPD severity grade on the BPD child's condition is matched.

[0151] The blood oxygen saturation may be an arterial blood oxygen saturation value.

[0152] The real-time fluctuation amplitude can be the dynamic change range of the blood oxygen saturation value within a preset time period.

[0153] Specifically, based on the monthly age distribution data, a preset age-weight mapping table (stores the mapping relationship between monthly age distribution data and condition impact weights, used to determine the impact weight of the child's age on the BPD child's condition) is queried through statistical analysis. The age range to which the child's age belongs is matched, and the impact weight of the child's age on the BPD child's condition is determined. Physiological data is analyzed to extract blood oxygen saturation within a preset time period (such as during EDP diagnosis and treatment), and the real-time fluctuation range of the BPD child's blood oxygen saturation is calculated using standard deviation.

[0154] According to the real-time fluctuation amplitude and BPD onset information, a preset basic lung function index weight mapping table established by the blood oxygen saturation fluctuation amplitude and the basic lung function index is queried (the mapping relationship between the combination of real-time fluctuation amplitude and BPD onset information and the weight of the impact of the disease is stored, which is used to determine the weight of the impact of the basic lung function index on the disease of BPD children. For example, when the real-time fluctuation amplitude is high and the BPD onset information is serious, the weight of the impact of the disease is high), and the weight of the impact of the basic lung function index on the disease of BPD children is determined.

[0155] According to the real-time fluctuation amplitude and BPD incidence information, a preset comorbidity number weight mapping table is queried, which is established by counting the probability of disease worsening of different comorbidity numbers under real-time fluctuation amplitudes (storing the mapping relationship between the combination conditions of the real-time fluctuation amplitude and the number of comorbidities and the disease impact weight, and is used to determine the disease impact weight of the number of comorbidities on the BPD child's disease. For example, when the real-time fluctuation amplitude is large and the BPD incidence information is complex, the disease impact weight increases), to determine the disease impact weight of the number of comorbidities on the BPD child's disease.

[0156] The child's age, real-time fluctuation amplitude, and BPD onset information were integrated, and the preset BPD severity grading weight mapping table established by multivariate regression analysis was queried (storing the mapping relationship between the child's age, real-time fluctuation amplitude, BPD onset information, and the weight of the disease impact, which is used to determine the weight of the BPD severity grading's impact on the BPD child's disease. For example, when the child is young, the real-time fluctuation amplitude is high, and the BPD onset information is severe, the disease impact weight is high), and the weight of the BPD severity grading's impact on the BPD child's disease was determined.

[0157] Through this solution, the weight of the impact of the child's age on the BPD child's condition is matched based on the monthly age distribution data, achieving quantitative assignment of the age factor and reflecting the differentiated impact of age on the condition. Physiological data is analyzed to determine the real-time fluctuation amplitude of the blood oxygen saturation of BPD children, converting dynamic physiological changes into calculable fluctuation parameters to eliminate subjective judgment bias. Based on the real-time fluctuation amplitude and BPD onset information, the weight of the impact of basic lung function indicators and the number of comorbidities on the condition of BPD children is matched, achieving real-time quantification of the impact of lung function on the condition, so that the contribution of the number of comorbidities to the condition is dynamically adjusted with blood oxygen stability. Based on the child's age, real-time fluctuation amplitude and BPD onset information, the weight of the impact of BPD severity grade on the condition of BPD children is matched to avoid the one-sidedness of a single grading standard.

[0158] Figure 3 This is a structural diagram of an external diaphragm pacing diagnosis and treatment effect evaluation system provided in one embodiment of the present application, such as Figure 3 As shown, the external diaphragm pacing diagnosis and treatment effect evaluation system 300 of this embodiment includes: an information acquisition module 301, a level determination module 302, a change analysis module 303, and an effect evaluation module 304.

[0159] The information acquisition module 301 is used to obtain the diagnosis and treatment information of the BPD child and the physiological data before and after receiving EDP diagnosis and treatment; a level determination module 302 for determining the individual functional level of the child with BPD based on the diagnosis and treatment information; a change analysis module 303 for determining changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level; The effect evaluation module 304 is used to comprehensively evaluate the EDP diagnosis and treatment effect based on the changes in the respiratory muscle function, the diaphragm function and the expectoration ability.

[0160] Optionally, when determining the individual functional level of the BPD child based on the diagnosis and treatment information, the level determination module 302 is configured to: Analyze the diagnosis and treatment information to determine the child's age, BPD severity level, number of comorbidities, and baseline lung function indicators; Obtaining BPD onset information; and matching the age of the child, the basic lung function index, the BPD severity grade, and the number of comorbidities with the weights of their respective impact on the condition of the BPD child based on the BPD onset information; Based on the BPD onset information, the child's age and the basic lung function index are converted into positive z-score values ​​respectively; The BPD severity grade and the number of comorbidities were converted into negative z-score values; The individual functional level of the BPD child is calculated and determined based on the disease impact weight, the positive z-score value, and the negative z-score value.

[0161] Optionally, when the level determination module 302 converts the child's age and the basic lung function index into positive z-score values ​​based on the BPD onset information, it is used to: Based on the BPD onset information, determine the mean age and standard deviation of BPD onset age; Determining the conversion of the positive z-score value corresponding to the age of the child according to the mean age of onset of BPD and the standard deviation of the age; Based on the BPD onset information, the mean and standard deviation of lung function indicators of children with the same period were determined; Determine the conversion of the positive z-score value corresponding to the basic pulmonary function index according to the pulmonary function index mean and the pulmonary function standard deviation.

[0162] Optionally, when the change analysis module 303 determines the changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level, it is configured to: Analyze the physiological data to determine the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment; The rate of change of respiratory muscle strength before and after treatment was determined based on the maximum inspiratory pressure and maximum expiratory pressure before and after treatment; Correcting the respiratory muscle strength change rate according to the individual functional level to determine the respiratory muscle function change of the BPD child; Analyzing the physiological data to determine the diaphragm thickness and diaphragm movement range before and after diagnosis and treatment; According to the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment are determined; Determine the diaphragm function changes of the BPD children based on the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment; Analyzing the physiological data to determine the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within a preset time period before and after diagnosis and treatment; The basal change rate of sputum discharge was determined based on the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within the preset time period.

[0163] Optionally, when determining the basal change rate of sputum discharge based on the peak cough flow rate before and after diagnosis and treatment and the sputum discharge volume within a preset period, the change analysis module 303 is used to: Analyzing the changes in diaphragmatic function to determine the diaphragmatic expectoration coordination level; The sputum discharge basal change rate is determined based on the diaphragmatic sputum discharge coordination level, the cough peak flow rate before and after diagnosis and treatment, and the sputum discharge volume within a preset time period.

[0164] Optionally, the external diaphragm pacing diagnosis and treatment effect evaluation system further includes a weight determination module 305, which is used to: Analyze the BPD incidence information and determine the monthly age distribution data of the affected group; Analyzing the monthly age distribution data and the age of the child to determine the skewness of the monthly age distribution; Determining the weight of the effect of the child's age on the condition of the BPD child according to the skewness of the monthly age distribution; Analyze the BPD onset information and determine the median lung function of children in the same period; Obtain functional baseline values ​​of healthy lung function; The weight of the impact of the basic lung function index on the condition of the BPD child is determined based on the median lung function of the children in the same period and the functional baseline value.

[0165] Optionally, the external diaphragm pacing diagnosis and treatment effect evaluation system further includes a diagnosis and treatment means determination module 306, which is used to: Determine the diagnostic and treatment equipment based on the age of the child; Based on the age of the child, analyze and determine the difficulty of diagnosis and treatment and the condition of the child during the diagnosis and treatment process; Determine auxiliary diagnosis and treatment methods based on the condition of the child and the difficulty of diagnosis and treatment.

[0166] Optionally, the external diaphragm pacing diagnosis and treatment effect evaluation system further includes a frequency and concentration determination module 307, which is used to: Determine the degree of compliance with instructions based on the age of the child; Determine the difficulty of inducing cough based on the child's condition; determining cough assistance means according to the degree of compliance with the instruction and the difficulty of inducing the cough; Based on the age and medical information of the child, the cough stimulation frequency and the concentration of the cough irritant in the cough assistive means are determined.

[0167] Optionally, when the level determination module 302 matches the weights of the child's age, the basic lung function index, the BPD severity grade, and the number of comorbidities on the BPD child's condition based on the BPD onset information, it is configured to: According to the monthly age distribution data, matching the weight of the impact of the child's age on the condition of the BPD child; Analyzing the physiological data to determine the real-time fluctuation amplitude of the blood oxygen saturation of the BPD child; According to the real-time fluctuation amplitude and the BPD onset information, the weights of the basic lung function index and the number of comorbidities affecting the condition of the BPD child are matched; According to the age of the child, the real-time fluctuation amplitude and the BPD onset information, the BPD severity grade is matched with the weight of the condition of the BPD child.

[0168] The system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A method for evaluating the diagnostic and therapeutic effect of external diaphragm pacing, characterized in that: include: Obtain the diagnosis and treatment information of children with BPD and their physiological data before and after EDP diagnosis and treatment; determining the individual functional level of the child with BPD based on the diagnosis and treatment information; Determining changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level; Based on the changes in respiratory muscle function, diaphragmatic function and expectoration ability, the EDP diagnosis and treatment effect is comprehensively evaluated.

2. The method according to claim 1, characterized in that Determining the individual functional level of the child with BPD based on the diagnosis and treatment information includes: Analyze the diagnosis and treatment information to determine the child's age, BPD severity level, number of comorbidities, and baseline lung function indicators; Obtaining BPD onset information; and matching the age of the child, the basic lung function index, the BPD severity grade, and the number of comorbidities with the weights of their respective impact on the condition of the BPD child based on the BPD onset information; Based on the BPD onset information, the child's age and the basic lung function index are converted into positive z-score values ​​respectively; The BPD severity grade and the number of comorbidities were converted into negative z-score values; The individual functional level of the BPD child is calculated and determined based on the disease impact weight, the positive z-score value, and the negative z-score value.

3. The method according to claim 2, characterized in that The step of converting the child's age and the basic lung function index into positive z-score values ​​based on the BPD onset information includes: Based on the BPD onset information, determine the mean age and standard deviation of BPD onset age; Determining the conversion of the positive z-score value corresponding to the age of the child according to the mean age of onset of BPD and the standard deviation of the age; Based on the BPD onset information, the mean and standard deviation of lung function indicators of children with the same period were determined; Determine the conversion of the positive z-score value corresponding to the basic pulmonary function index according to the pulmonary function index mean and the pulmonary function standard deviation.

4. The method according to claim 1, wherein Determining changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level includes: Analyze the physiological data to determine the maximum inspiratory pressure and maximum expiratory pressure before and after diagnosis and treatment; The rate of change of respiratory muscle strength before and after treatment was determined based on the maximum inspiratory pressure and maximum expiratory pressure before and after treatment; Correcting the respiratory muscle strength change rate according to the individual functional level to determine the respiratory muscle function change of the BPD child; Analyzing the physiological data to determine the diaphragm thickness and diaphragm movement range before and after diagnosis and treatment; According to the diaphragm thickness and diaphragm movement amplitude before and after diagnosis and treatment, the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment are determined; Determine the diaphragm function changes of the BPD children based on the diaphragm thickness change rate and diaphragm movement change rate before and after diagnosis and treatment; Analyzing the physiological data to determine the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within a preset time period before and after diagnosis and treatment; The basal change rate of sputum discharge was determined based on the peak cough flow rate before and after diagnosis and treatment and the amount of sputum discharged within the preset time period.

5. The method according to claim 4, characterized in that Determining the sputum discharge basic change rate based on the cough peak flow rate before and after diagnosis and treatment and the sputum discharge volume within a preset period of time includes: Analyzing the changes in diaphragmatic function to determine the diaphragmatic expectoration coordination level; The sputum discharge basal change rate is determined based on the diaphragmatic sputum discharge coordination level, the cough peak flow rate before and after diagnosis and treatment, and the sputum discharge volume within a preset time period.

6. The method according to claim 2, characterized in that According to the BPD onset information, matching the age of the child and the basic lung function index with the weight of the condition of the BPD child includes: Analyze the BPD incidence information and determine the monthly age distribution data of the affected group; Analyzing the monthly age distribution data and the age of the child to determine the skewness of the monthly age distribution; Determining the weight of the effect of the child's age on the condition of the BPD child according to the skewness of the monthly age distribution; Analyze the BPD onset information and determine the median lung function of children in the same period; Obtain functional baseline values ​​of healthy lung function; The weight of the impact of the basic lung function index on the condition of the BPD child is determined based on the median lung function of the children in the same period and the functional baseline value.

7. The method according to claim 2, characterized in that Before obtaining the physiological data of the BPD child before and after receiving EDP diagnosis and treatment, the method further includes: Determine the diagnostic and treatment equipment based on the age of the child; Based on the age of the child, analyze and determine the difficulty of diagnosis and treatment and the condition of the child during the diagnosis and treatment process; Determine auxiliary diagnosis and treatment methods based on the condition of the child and the difficulty of diagnosis and treatment.

8. The method according to claim 7, characterized in that Before obtaining the physiological data of the BPD child before and after receiving EDP diagnosis and treatment, the method further includes: Determine the degree of compliance with instructions based on the age of the child; Determine the difficulty of inducing cough based on the child's condition; determining cough assistance means according to the degree of compliance with the instruction and the difficulty of inducing the cough; Based on the age and medical information of the child, the cough stimulation frequency and the concentration of the cough irritant in the cough assistive means are determined.

9. The method according to claim 6, characterized in that According to the BPD onset information, matching the weights of the child's age, the basic lung function index, the BPD severity grade, and the number of comorbidities on the condition of the BPD child includes: According to the monthly age distribution data, matching the weight of the impact of the child's age on the condition of the BPD child; Analyzing the physiological data to determine the real-time fluctuation amplitude of the blood oxygen saturation of the BPD child; According to the real-time fluctuation amplitude and the BPD onset information, the weights of the basic lung function index and the number of comorbidities affecting the condition of the BPD child are matched; According to the age of the child, the real-time fluctuation amplitude and the BPD onset information, the BPD severity grade is matched with the weight of the condition of the BPD child.

10. A system for evaluating the diagnosis and treatment effect of external diaphragm pacing, characterized in that: The method as claimed in any one of claims 1 to 9 comprises: The information acquisition module is used to obtain the diagnosis and treatment information of children with BPD and their physiological data before and after receiving EDP diagnosis and treatment; a level determination module, configured to determine the individual functional level of the child with BPD based on the diagnosis and treatment information; a change analysis module, configured to determine changes in respiratory muscle function, diaphragmatic function, and expectoration ability of the BPD child based on the physiological data and the individual functional level; The effect evaluation module is used to comprehensively evaluate the EDP diagnosis and treatment effect based on the changes in the respiratory muscle function, the diaphragm function and the expectoration ability.

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