CN114711749A - Lung function state classification method based on quantitative report template - Google Patents
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/091—Measuring volume of inspired or expired gases, e.g. to determine lung capacity
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
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- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Abstract
The invention discloses a lung function state classification method based on a quantitative report template, which comprises the steps of determining lung function classifications in a lung function examination project, determining detection elements matched with each lung function classification, planning the state grade of each lung function classification, and dividing the numerical range corresponding to each state grade; calculating the correlation value of each detection element to the matched lung function classification according to the detection element value corresponding to each lung function classification in a first weighted average mode; carrying out cumulative sum calculation on the correlation values of the detection element numerical values to obtain the current function distribution value of each lung function classification and determine the state grade of the lung function classification; and carrying out secondary weighted average on the influence weight of the lung function parenchymal damage degree according to the lung function classification of different state grades to obtain a liver score total value reflecting the liver parenchymal damage, and determining the whole liver state based on the liver score total value. The invention can help medical personnel to quickly obtain an accurate lung function diagnosis result.
Description
Technical Field
The invention relates to the technical field of lung function determination, in particular to a lung function state classification method based on a quantitative report template.
Background
Lung function measurement (lung function test) refers to a process of evaluating the condition of the lung function of a human body by measuring some indexes of the respiratory system. The method is widely applied to the identification of the health condition of the human body and the evaluation of the working capacity. Commonly used measures of lung function include lung volume, tidal volume, lung capacity, residual volume, functional residual volume, lung ventilation, respiratory rate, partial pressure of oxygen, partial pressure of carbon dioxide, respiratory quotient, and the like. This is typically done by a pulmonary function tester or a polygraph. The indexes of lung function measurement are affected by various factors, and therefore, the indexes are often greatly different. Variations such as age, gender, size, physical condition and situation can affect the measurement. The lung function is generally evaluated comprehensively according to a plurality of indexes. The condition of lung function directly affects the condition of energy metabolism of human body, and can reflect the quality and working capacity of human body.
The existing lung function state classification based on the quantitative report template is mostly only set with a plurality of lung function classifications, detection elements of a lung function measuring instrument are directly or indirectly processed by a formula to obtain the lung function classifications, only some inspection data can be obtained, and the overall index and the health condition of the lung function are not further calculated.
Disclosure of Invention
The invention aims to provide a lung function state classification method based on a quantitative report template, which aims to solve the technical problems that in the prior art, detection elements of a lung function measuring instrument are directly or indirectly processed by a formula to obtain lung function classification, only some inspection data can be obtained, and the overall index and the health condition of the lung function are not further calculated and processed.
In order to solve the technical problems, the invention specifically provides the following technical scheme:
a lung function state classification method based on a quantitative report template comprises the following steps:
step 100, determining lung function classifications in a lung function examination project, determining detection elements matched with each lung function classification, planning a state grade of each lung function classification, and dividing a numerical range corresponding to each state grade;
step 200, calculating an influence value of the influence of the distribution range of the current measured value of each detection element according to the detection element value corresponding to each lung function classification in a first weighted average mode, and then calculating the association value of each detection element on the matched lung function classification;
step 300, performing cumulative sum calculation on the correlation values of the detection element numerical values to obtain the current function distribution value of each lung function classification, and determining a state grade matched with the current function distribution value of the lung function classification;
step 400, determining the number of lung function classifications corresponding to the state grades influencing the liver health according to the state grades of all the lung function classifications, performing second weighted average on the influence weights of the lung function substantial damage degrees according to the lung function classifications of different state grades to obtain a liver score total value reflecting the liver substantial damage, and determining the liver overall state based on the liver score total value.
As a preferred aspect of the present invention, in the step 100, the status levels of the lung function classifications are classified into a level I, a level II, a level III, and so on according to the numerical range of each lung function classification, wherein as the status level of the lung function classification is higher, the lung function index corresponding to the lung function classification is worse.
As a preferred aspect of the present invention, the lung function classification includes integrated lung capacity, surface lung tissue expansion, and lung diffusion function;
the integrated vital capacity comprises vital capacity, forced vital capacity and forced expiratory capacity in one second, wherein the vital capacity refers to the maximum expired air volume after the maximum inspiration; the forced vital capacity refers to the total volume of the breath which is forced to exhale at the fastest speed after the breath is deeply inhaled to the maximum extent;
the surface lung tissue expansion refers to the ratio of residual air quantity in the lung after deep respiratory gas to total lung quantity, and represents the retention air quantity in the alveolus;
the lung dispersion function refers to the ratio of the amount of carbon oxide dispersion to the alveolar ventilation to diagnose the strength of the lung dispersion function.
As a preferred aspect of the present invention, in step 200, the calculation method for calculating the correlation value of each of the detection element values is:
step 201, determining a standard numerical range of each detection element, and determining a central value of each detection element;
step 202, calculating the absolute value of the difference between the current measurement value of each detection element and the central value of the corresponding standard numerical range;
step 203, determining the influence degree of the current measurement value of the detection element on the lung function according to the distribution progression of the difference absolute value, determining the primary influence weight of the difference absolute value, and calculating the influence value of each detection element based on the primary influence weight and the difference absolute value.
As a preferred scheme of the present invention, based on an influence weight of each detection element on the matched lung function classification, a first weighted average is performed on an influence value of each detection element and a corresponding influence weight, and a correlation value of a numerical value of each detection element is calculated.
As a preferred aspect of the present invention, in step 300, a total of influence values of a plurality of detection elements matching each of the lung function classifications is calculated, and according to a numerical range corresponding to the state level of each of the lung function classifications, a numerical range in which the total of influence values is located is determined, thereby determining a state level matching the numerical value of the lung function classification.
As a preferred aspect of the present invention, in step 400, the integrated lung capacity, surface lung tissue expansion and lung diffusion function have different degrees of substantial lung function impairment, wherein when the state level of the lung function classification reaches level III and above, the state level of the lung function classification affects the lung function index.
As a preferred aspect of the present invention, in step 400, when the status levels of all the lung function classifications do not reach level III, the influence weight of the status level of each lung function classification at that time on the substantial lung function damage degree is 0, and when the status level of at least one of the lung function classifications reaches level III, the influence weight on the substantial lung function damage degree is determined according to the status level of the lung function classification, wherein,
the higher the status level of a lung function classification, the more heavily the lung function classification has a weight on the extent of substantial impairment of lung function.
As a preferred embodiment of the present invention, in step 400, the second weighted average of the influence weights of the lung function classifications with different status levels on the degree of substantial lung function impairment is calculated by: first order influence weight of the state grade of the lung function classification on the lung function parenchymal damage degree is determined, and then second order influence weight of the lung function classification on the lung function parenchymal damage degree is determined.
As a preferred embodiment of the present invention, determining an influence weight of a state level of a lung function classification on a degree of substantial lung function impairment, wherein if the influence weight is based on a level III, and the state level of each lung function classification is increased by one level, the influence weight is increased based on the reference influence weight;
calculating a first-order influence value of the state grade of the lung function classification on the liver parenchymal damage by taking the influence weight of the state grade of the lung function classification on the lung function parenchymal damage degree as a first-order influence weight;
and (4) taking the influence weight of the lung function classification on the liver parenchymal damage as a second-order influence weight, and calculating a liver score total value reflecting the liver parenchymal damage by using the first-order influence value and the second-order influence weight.
Compared with the prior art, the invention has the following beneficial effects:
the method determines the current lung function state of the patient and the corresponding classification of the lung function state according to the lung function detection elements, unifies the values of all scattered detection elements by utilizing the value distribution of different detection elements and the weight of the influence on the lung function, and finally obtains a lung function index with indexation and only a small amount of data, thereby helping medical personnel to quickly obtain an accurate lung function diagnosis result.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
Fig. 1 is a flowchart illustrating a lung function state classification method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
As shown in fig. 1, the present invention provides a method for classifying lung function states based on a quantitative report template, and the main purpose of the present embodiment is to determine the current lung function state of a patient and the corresponding classification of lung function states based on values of lung function detection elements, such as lung volume, tidal volume, lung capacity, residual volume, functional residual volume, lung ventilation volume, respiratory rate, oxygen partial pressure, carbon dioxide partial pressure, respiratory quotient, etc., and the present embodiment unifies values of all scattered detection elements by using the value distribution of different detection elements and the weight of influence on lung function, so as to finally obtain a lung function index with index and only a small amount of data, thereby helping medical staff to obtain an accurate lung function diagnosis result quickly.
The method specifically comprises the following steps:
step 100, determining lung function classifications in the lung function examination items, determining detection elements matched with each lung function classification, planning the state grade of each lung function classification, and dividing the numerical range corresponding to each state grade.
And classifying the state grades of the lung function classifications into I grade, II grade, III grade, IV grade … … according to the numerical range of each lung function classification, and so on, wherein the lung function indexes corresponding to the lung function classifications are worse as the state grades of the lung function classifications are higher.
The lung function classification includes integrated vital capacity, surface lung tissue expansion, lung dispersion function.
The integrated vital capacity includes Vital Capacity (VC), Forced Vital Capacity (FVC), and forced expiratory volume per second (FVC).
Vital Capacity (VC) refers to the maximum volume exhaled after maximum inhalation; forced Vital Capacity (FVC) means that the patient can exhale all air volume at the fastest speed after inhaling air deeply to the maximum extent, can reflect the expiratory resistance of a large airway, is mainly used for judging chronic bronchitis and bronchial asthma and whether the patient has emphysema, and if the forced expiratory volume (FVC) in one second is reduced and is lower than 80% of a normal index, the patient often indicates the obstruction of restrictive ventilation function.
The superficial lung tissue expansion is the ratio of residual air volume (RV) in lung after deep respiratory air to total lung volume (TLC), and is used for diagnosing emphysema, wherein the ratio represents the retention air volume in alveolus.
The lung diffusion function refers to the ratio of carbon oxide diffusion (DLco) to alveolar Ventilation (VA) to diagnose the strength of the lung diffusion function.
Therefore, since each lung function classification is directly measured by the lung function measuring instrument or the multi-lead physiological instrument or is calculated from the measured detection elements, in the present embodiment, when the lung function state classification is performed in the present embodiment, the final lung function health value is calculated by a weighted average method for a plurality of lung function classifications.
And 200, calculating the influence value of the influence of the distribution range of the current measured value of each detection element on the detection element value corresponding to each lung function classification according to a first weighted average mode, and then calculating the correlation value of each detection element on the matched lung function classification.
The detection elements corresponding to the Vital Capacity (VC) are the maximum expired air volume obtained by a lung function tester after maximum inspiration, the detection elements corresponding to the Forced Vital Capacity (FVC) are all expired air volume with the highest forced speed after deep inspiration to the maximum extent, the detection elements corresponding to the surface lung tissue expansion are the residual air volume (RV) in the lung and the total lung volume (TLC), and the detection elements corresponding to the lung dispersion function are carbon oxide dispersion (DLco) and alveolar Ventilation (VA).
Most of the prior art only calculates the step 100, and the overall influence value of the data obtained by classifying and calculating the lung functions and the health status of the lung functions are not directly evaluated, so that the medical staff needs to analyze the data again, and the patient cannot directly and quickly obtain the evaluation result of the lung functions.
In the embodiment, the quantitative data of the lung function classification is subjected to secondary analysis processing, the current lung function state of the patient and the corresponding lung function state classification are determined according to the lung function detection element, the influence of each lung function classification on the lung health and the state classification of each lung function classification are further determined, a total liver score value reflecting the substantial damage of the liver is finally determined, and the overall liver state is determined based on the total liver score value.
In step 200, the calculation method for calculating the correlation value of each detection element value is as follows:
step 201, determining a standard value range of each detection element, and determining a central value of each detection element, wherein the standard value range of the lung function detection is closely related to the age, sex and shape of the currently detected patient, and the standard value range of each detection element is obtained based on the age, sex and shape of the patient and by using big data statistics.
Step 202, calculating the absolute value of the difference between the current measured value of each detection element and the central value of the corresponding standard value range.
And 203, determining the influence degree of the current measuring value of the detection element on the lung function according to the distribution progression of the difference absolute value, determining the primary influence weight of the difference absolute value, and calculating the influence value of each detection element based on the primary influence weight and the difference absolute value.
And carrying out first weighted average on the influence value of each detection element and the corresponding influence weight based on the influence weight of each detection element on the matched lung function classification, and calculating the association value of each detection element value.
Therefore, in the embodiment, after the difference absolute value of each lung function classification is calculated, the primary influence weight is determined according to the distribution series of the difference absolute values, and then the product of the primary influence weight and the difference absolute value is used as the influence value of each detection element.
Because the surface lung tissue expansion and lung dispersion functions are the ratio calculation modes of detection elements, the residual air volume (RV) in the lung after the corresponding deep breathing, the total lung volume (TLC), the carbon oxide dispersion (DLco) and the alveolar Ventilation (VA) also have a standard numerical range, and in this way, the surface lung tissue expansion and lung dispersion functions can only be in a standard range.
Therefore, the present embodiment identifies the influence of each detection element on the matched lung function classification by identifying the influence value of each detection element, which corresponds to the influence of each detection element on the lung function measurement from a microscopic viewpoint.
And step 300, performing cumulative sum calculation on the correlation values of the detection element numerical values to obtain the current function distribution value of each lung function classification, and determining the state grade matched with the current function distribution value of the lung function classification.
In the present embodiment, each of the lung function classifications (i.e., the integrated lung capacity, the surface lung tissue expansion, and the lung diffusion function) is classified into different state grades, and each of the state grades of the integrated lung capacity, the surface lung tissue expansion, and the lung diffusion function corresponds to a numerical range calculated according to the cumulative sum of the associated values.
In step 300, the sum of the influence values of the plurality of detection elements matching each lung function classification is calculated, and according to the numerical range corresponding to the state level of each lung function classification, the numerical range in which the sum of the influence values is located is determined, thereby determining the state level matching the numerical value of the lung function classification.
That is, the current function distribution value span of each lung function classification is different, the corresponding status levels are different, for example, (a, b) is the I level of the lung function classification, (b, c) is the II level of the lung function classification, and so on.
Step 400, determining the number of lung function classifications corresponding to the state grades influencing the liver health according to the state grades of all the lung function classifications, performing second weighted averaging on the influence weights of the lung function substantial damage degrees according to the lung function classifications of different state grades to obtain a liver score total value reflecting the liver substantial damage, and determining the liver overall state based on the liver score total value.
The integrated lung capacity, the surface lung tissue expansion and the lung diffusion function have different damage degrees to the lung function, wherein when the state grade of the lung function classification reaches the level III and above the level III, the state grade of the lung function classification influences the lung function index.
In step 400, when the state levels of all the lung function classifications do not reach level III, the influence weight of the state level of each lung function classification at that time on the substantial lung function damage degree is 0, and when the state level of at least one lung function classification reaches level III, the influence weight on the substantial lung function damage degree is determined according to the state level of the lung function classification, wherein the higher the state level of the lung function classification is, the higher the influence weight on the substantial lung function damage degree of the lung function classification is.
In step 400, the second weighted average of the influence weights of the lung function classification according to different state levels on the substantial lung function damage degree is calculated as follows: first order influence weight of the state grade of the lung function classification on the lung function parenchymal damage degree is determined, and then second order influence weight of the lung function classification on the lung function parenchymal damage degree is determined.
And determining the influence weight of the state grade of the lung function classification on the substantial damage degree of the lung function, and increasing the influence weight on the basis of the reference influence weight by taking the grade III as the reference influence weight and increasing the state grade of each lung function classification by one grade.
And calculating a first-order influence value of the state grade of the lung function classification on the liver parenchymal damage by taking the influence weight of the state grade of the lung function classification on the lung function parenchymal damage degree as a first-order influence weight.
And (4) taking the influence weight of the lung function classification on the liver parenchymal damage as a second-order influence weight, and calculating a liver score total value reflecting the liver parenchymal damage by using the first-order influence value and the second-order influence weight.
That is, the degree of substantial damage of each lung function classification (i.e., the integrated lung capacity, the surface lung tissue expansion, and the lung diffusion function) to the lung function is different, the influence coefficient of each lung function classification to the lung damage is used to perform the normalization total processing on all the detection elements to obtain a total value related to the lung function, and the health condition of the lung is judged according to the total value, so that the examination result can be obtained more directly.
Therefore, the present embodiment determines the current lung function state of the patient and the corresponding classification of the lung function state according to the lung function detecting elements, and the present embodiment unifies the values of all scattered detecting elements by using the value distribution of different detecting elements and the weight of the influence on the lung function, and finally obtains a lung function index with index and only a small amount of data, thereby helping medical staff to obtain an accurate lung function diagnosis result quickly.
The above embodiments are only exemplary embodiments of the present application, and are not intended to limit the present application, and the protection scope of the present application is defined by the claims. Various modifications and equivalents may be made by those skilled in the art within the spirit and scope of the present application and such modifications and equivalents should also be considered to be within the scope of the present application.
Claims (10)
1. A lung function state classification method based on a quantitative report template is characterized by comprising the following steps:
step 100, determining lung function classifications in a lung function examination project, determining detection elements matched with each lung function classification, planning a state grade of each lung function classification, and dividing a numerical range corresponding to each state grade;
step 200, calculating an influence value of the influence of the distribution range of the current measured value of each detection element according to the detection element value corresponding to each lung function classification in a first weighted average mode, and then calculating the association value of each detection element on the matched lung function classification;
step 300, performing cumulative sum calculation on the correlation values of the detection element numerical values to obtain the current function distribution value of each lung function classification, and determining a state grade matched with the current function distribution value of the lung function classification;
step 400, determining the number of lung function classifications corresponding to the state grades influencing the liver health according to the state grades of all the lung function classifications, performing second weighted average on the influence weights of the lung function substantial damage degrees according to the lung function classifications of different state grades to obtain a liver score total value reflecting the liver substantial damage, and determining the liver overall state based on the liver score total value.
2. The method for classifying lung function state based on quantitative report template as claimed in claim 1, wherein: in step 100, the status levels of the lung function classifications are classified into a level I, a level II, a level III, and so on according to the numerical range of each lung function classification, wherein as the status level of the lung function classification is higher, the lung function index corresponding to the lung function classification is worse.
3. The method for classifying lung function state based on quantitative report template as claimed in claim 1, wherein: the lung function classification comprises integrated vital capacity, surface lung tissue expansion and lung diffusion functions;
the integrated vital capacity comprises vital capacity, forced vital capacity and forced expiratory capacity in one second, wherein the vital capacity refers to the maximum expired air volume after the maximum inspiration; the forced vital capacity refers to the total volume of the breath which is forced to exhale at the fastest speed after the breath is deeply inhaled to the maximum extent;
the surface lung tissue expansion refers to the ratio of residual air quantity in the lung after deep respiratory gas to total lung quantity, and represents the retention air quantity in the alveolus;
the lung diffusion function refers to the ratio of the amount of carbon oxide diffusion to the amount of alveolar ventilation to diagnose the strength of the lung diffusion function.
4. The method for classifying lung function state based on quantitative report template as claimed in claim 1, wherein: in step 200, the calculation method for calculating the correlation value of each detection element value is as follows:
step 201, determining a standard numerical range of each detection element, and determining a central value of each detection element;
step 202, calculating the absolute value of the difference between the current measurement value of each detection element and the central value of the corresponding standard numerical range;
step 203, determining the influence degree of the current measurement value of the detection element on the lung function according to the distribution progression of the difference absolute value, determining the primary influence weight of the difference absolute value, and calculating the influence value of each detection element based on the primary influence weight and the difference absolute value.
5. The method of claim 4, wherein the classification of lung function status based on the quantitative report template comprises: and carrying out first weighted average on the influence value of each detection element and the corresponding influence weight based on the influence weight of each detection element on the matched lung function classification, and calculating the association value of each detection element value.
6. The method of claim 5, wherein the lung function state classification method based on the quantitative report template comprises: in step 300, the sum of the influence values of the plurality of detection elements matching each of the lung function classifications is calculated, and according to the numerical range corresponding to the state level of each of the lung function classifications, the numerical range in which the sum of the influence values is located is determined, thereby determining the state level matching the numerical value of the lung function classification.
7. The method of claim 3, wherein the lung function state classification method based on the quantitative report template comprises: in step 400, the integrated lung capacity, surface lung tissue expansion and lung diffusion function have different degrees of lung function substantial damage, wherein when the state grade of the lung function classification reaches level III and above level III, the state grade of the lung function classification affects the lung function index.
8. The method of claim 7, wherein the lung function state classification method based on the quantitative report template comprises: in step 400, when the status levels of all the lung function classifications do not reach level III, the influence weight of the status level of each lung function classification at the moment on the substantial lung function damage degree is 0, and when the status level of at least one of the lung function classifications reaches level III, the influence weight on the substantial lung function damage degree is determined according to the status level of the lung function classification, wherein,
the higher the status level of a lung function classification, the more heavily the lung function classification has a weight on the extent of substantial impairment of lung function.
9. The method of claim 7, wherein the lung function state classification method based on the quantitative report template comprises: in step 400, the second weighted average of the influence weights of the lung function classifications with different state levels on the substantial lung function impairment degree is calculated as follows: first order influence weight of the state grade of the lung function classification on the lung function parenchymal damage degree is determined, and then second order influence weight of the lung function classification on the lung function parenchymal damage degree is determined.
10. The method of claim 9, wherein the lung function state classification method based on the quantitative report template comprises: determining the influence weight of the state grade of the lung function classification on the substantial damage degree of the lung function, taking the grade III as a reference influence weight, and increasing the influence weight on the basis of the reference influence weight if the state grade of each lung function classification is increased by one grade;
calculating a first-order influence value of the state grade of the lung function classification on the liver parenchymal damage by taking the influence weight of the state grade of the lung function classification on the lung function parenchymal damage degree as a first-order influence weight;
and (4) taking the influence weight of the lung function classification on the liver parenchymal damage as a second-order influence weight, and calculating a liver score total value reflecting the liver parenchymal damage by using the first-order influence value and the second-order influence weight.
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| CN115223675A (en) * | 2022-09-20 | 2022-10-21 | 深圳市健怡康医疗器械科技有限公司 | Pulmonary function detection data processing system based on summarizing type grading |
| CN116823767A (en) * | 2023-06-27 | 2023-09-29 | 无锡市人民医院 | Method for judging lung transplantation activity grade based on image analysis |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115223675A (en) * | 2022-09-20 | 2022-10-21 | 深圳市健怡康医疗器械科技有限公司 | Pulmonary function detection data processing system based on summarizing type grading |
| CN116823767A (en) * | 2023-06-27 | 2023-09-29 | 无锡市人民医院 | Method for judging lung transplantation activity grade based on image analysis |
| CN116823767B (en) * | 2023-06-27 | 2024-03-01 | 无锡市人民医院 | Method for judging lung transplantation activity grade based on image analysis |
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