Device, method and equipment for screening risk of slight hepatic encephalopathy and medium

Abstract

The invention relates to a slight hepatic encephalopathy risk screening device, method and equipment and a medium, and the device comprises a basic information obtaining module which is used for obtaining the basic information of a subject; the detection parameter acquisition module is used for acquiring detection parameters of a subject; the nutrition risk acquisition module is used for scoring the nutrition risk of the subject and determining the nutrition risk condition of the subject according to the scoring result; the risk screening module is used for inputting the basic information, the detection parameters and the nutrition risk condition of the subject into a slight hepatic encephalopathy risk model to obtain a slight hepatic encephalopathy risk condition of the subject; wherein the slight hepatic encephalopathy risk model is established based on a neural network and comprises an input layer, two hidden layers and an output layer. According to the method, the assessment result of the illness risk of the patient can be quickly and accurately obtained under the condition that subjective influence of a researcher or a subject is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of risk screening for mild hepatic encephalopathy, and in particular to a device, method, equipment and medium for risk screening for mild hepatic encephalopathy. Background Art

[0002] Hepatic encephalopathy is a neuropsychiatric syndrome secondary to severe liver dysfunction or portal vein-systemic shunt abnormalities. Its early stage is called minimal hepatic encephalopathy (MHE), which is one of the signs of rapid progression and poor prognosis of cirrhosis. Cognitive impairment at this stage can only be detected through specific and measurable tests. Domestic and foreign guidelines recommend the popularization of testing for patients with chronic liver disease. The existing testing methods mainly include: neuropsychological testing, neuroelectrophysiological testing and brain imaging examinations. Limited by the accessibility and operability of the above-mentioned testing methods, as well as the shortcomings of medical resource consumption and patient acceptance, MHE testing has not yet been used as a routine diagnosis and treatment for routine examinations and long-term follow-up of patients with chronic liver diseases such as cirrhosis. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a risk screening device, method, equipment and medium for mild hepatic encephalopathy, which can quickly and accurately obtain the assessment results of the patient's disease risk without being subjectively influenced by researchers or subjects.

[0004] The technical solution adopted by the present invention to solve the technical problem is: to provide a risk screening device for mild hepatic encephalopathy, comprising:

[0005] A basic information acquisition module is used to obtain the basic information of the subject;

[0006] A detection parameter acquisition module, used to obtain the detection parameters of the subject;

[0007] A nutrition risk acquisition module is used to score the nutrition risk of the subject and determine the nutrition risk status of the subject based on the scoring result;

[0008] The risk screening module is used to input the basic information, test parameters and nutritional risk status of the subject into the mild hepatic encephalopathy risk model to obtain the mild hepatic encephalopathy risk status of the subject; wherein the mild hepatic encephalopathy risk model is established based on a neural network, including an input layer, two hidden layers and an output layer.

[0009] The basic information of the subject includes the age of the subject, whether the subject has a history of diabetes, whether the subject has infection, whether the subject has renal insufficiency, and whether the subject has electrolyte disorder.

[0010] Whether the subject is infected is determined by the subject's clinical infection symptoms or test results. When the subject has clinical infection symptoms or the test results show evidence supporting infection, the subject is infected; when the subject does not have clinical infection symptoms and the test results show no evidence supporting infection, the subject is not infected.

[0011] Whether the subject has renal insufficiency is judged by the estimated glomerular filtration rate of the subject. When the estimated glomerular filtration rate of the subject is less than the renal function judgment threshold, the subject has renal insufficiency. When the estimated glomerular filtration rate of the subject is greater than or equal to the renal function judgment threshold, the subject does not have renal insufficiency.

[0012] Whether the subject has electrolyte disorder is judged by the blood sodium and blood potassium of the subject. When the blood sodium of the subject is less than the blood sodium threshold or the blood potassium of the subject is less than the blood potassium threshold, the subject has electrolyte disorder. When the blood sodium of the subject is greater than or equal to the blood sodium threshold and the blood potassium of the subject is greater than or equal to the blood potassium threshold, the subject does not have electrolyte disorder.

[0013] The test parameters of the subject include hemoglobin, total bilirubin, serum albumin, international normalized ratio, and plasma ammonia.

[0014] The nutrition score module includes:

[0015] A scoring unit, used to score the nutritional risk of the subject using the NRS2002 nutritional risk screening form;

[0016] A judging unit, used to judge whether the nutrition risk score of the subject exceeds a threshold;

[0017] The determination unit is used to determine that the subject has a nutritional risk when the nutritional risk score of the subject exceeds a threshold value, and to determine that the subject does not have a nutritional risk when the nutritional risk score of the subject does not exceed the threshold value.

[0018] The technical solution adopted by the present invention to solve the technical problem is: to provide a method for screening the risk of mild hepatic encephalopathy, comprising the following steps:

[0019] Obtain basic information of the subjects;

[0020] Obtaining test parameters of the subject;

[0021] Score the nutritional risk of the subject and determine the nutritional risk status of the subject based on the score results;

[0022] The basic information, test parameters and nutritional risk status of the subject are input into the mild hepatic encephalopathy risk model to obtain the mild hepatic encephalopathy risk status of the subject; wherein the mild hepatic encephalopathy risk model is established based on a neural network, including an input layer, two hidden layers and an output layer.

[0023] The technical solution adopted by the present invention to solve its technical problem is: to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned mild hepatic encephalopathy risk screening method when executing the computer program.

[0024] The technical solution adopted by the present invention to solve its technical problem is: providing a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned mild hepatic encephalopathy risk screening method are implemented.

[0025] Beneficial Effects

[0026] Due to the adoption of the above-mentioned technical scheme, the present invention has the following advantages and positive effects compared with the prior art: the present invention implements the assessment of the risk of the subject's disease by inputting several objective indicators of the subject into a risk model of mild hepatic encephalopathy based on a neural network. This method helps the clinician make rapid and accurate predictions through the input of objective parameters. According to the screening results, diagnostic tests can be further implemented on high-risk individuals, and active specialist intervention can be carried out to prevent them from further developing into overt hepatic encephalopathy. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flow chart of a method for screening risk of mild hepatic encephalopathy according to a first embodiment of the present invention;

[0028] Figure 2 : is a ROC curve diagram of the risk model of mild hepatic encephalopathy in the first embodiment of the present invention. DETAILED DESCRIPTION

[0029] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0030] The first embodiment of the present invention relates to a method for screening risk of mild hepatic encephalopathy, such as Figure 1 As shown, the following steps are included:

[0031] Step 1: Obtain the basic information of the subjects.

[0032] In this step, the basic information of the subject includes the subject's age, whether the subject has a history of diabetes, whether the subject has an infection (including: abdominal infection, respiratory tract infection, biliary tract infection, urinary tract infection, bloodstream infection, gastrointestinal infection, and skin and soft tissue infection, etc.), whether the subject has renal insufficiency, and whether the subject has electrolyte imbalance.

[0033] Among them, whether the subject is infected is judged by the subject's clinical infection symptoms (for example, fever, cough, abdominal pain and diarrhea, frequent urination and urgency, etc.) or test results (for example, routine or culture results of blood, sputum, feces, urine, etc.). When the subject has clinical infection symptoms or the test results show evidence supporting infection, the subject is infected; when the subject does not have clinical infection symptoms and the test results show no evidence supporting infection, the subject is not infected.

[0034] Whether the subject has renal insufficiency can be determined by the estimated glomerular filtration rate of the subject. When the estimated glomerular filtration rate of the subject is less than the renal function determination threshold, the subject has renal insufficiency. When the estimated glomerular filtration rate of the subject is greater than or equal to the renal function determination threshold, the subject does not have renal insufficiency. In this embodiment, the renal function determination threshold can be 90 ml·min -1 1.73m 2 .

[0035] Whether the subject has electrolyte disorder can be judged by the subject's blood sodium and blood potassium. When the subject's blood sodium is less than the blood sodium threshold or the subject's blood potassium is less than the blood potassium threshold, the subject has electrolyte disorder. When the subject's blood sodium is greater than or equal to the blood sodium threshold and the subject's blood potassium is greater than or equal to the blood potassium threshold, the subject does not have electrolyte disorder. In this embodiment, the blood sodium threshold can be 135mmol / L, and the blood potassium threshold can be 3.5mmol / L.

[0036] Step 2, obtaining the test parameters of the subject. In this step, the test parameters of the subject include hemoglobin, total bilirubin, serum albumin, international normalized ratio, and plasma ammonia.

[0037] Step 3, scoring the subject's nutritional risk and determining the subject's nutritional risk status based on the scoring result.

[0038] In this step, the NRS2002 Nutritional Risk Screening Table is used to score the nutritional risk of the subject. When the nutritional risk score of the subject exceeds a threshold value (e.g., 2 points), it is determined that the subject has a nutritional risk. When the nutritional risk score of the subject does not exceed the threshold value (e.g., 2 points), it is determined that the subject does not have a nutritional risk. Among them, the NRS2002 Nutritional Risk Screening Table contains three parts: disease score, nutritional status, and age score. Among them, the disease score part is multiple choice, and when the total score reaches 3 points, it will no longer increase; the nutritional status is not divided into single choice, and it is not mandatory; the age score part is single choice, and it is mandatory.

[0039] Step 4: input the basic information, test parameters and nutritional risk status of the subject into the mild hepatic encephalopathy risk model to obtain the mild hepatic encephalopathy risk status of the subject.

[0040] In this embodiment, the risk model of mild hepatic encephalopathy is established based on a neural network, which includes an input layer, two hidden layers and an output layer, wherein the number of nodes in the first hidden layer is 8, and the number of nodes in the second hidden layer is 6.

[0041] The data input into the input layer of the risk model for mild hepatic encephalopathy include the age of the subject, whether the subject has a history of diabetes (if there is a history of diabetes, the input is "1", otherwise the input is "0"), whether the subject has an infection (if there is an infection, the input is "1", otherwise the input is "0"), whether the subject has renal insufficiency (if there is renal insufficiency, the input is "1", otherwise the input is "0"), whether the subject has electrolyte disorder (if there is electrolyte disorder, the input is "1", otherwise the input is "0"), hemoglobin, total bilirubin, serum albumin, international normalized ratio, plasma ammonia, and the nutritional risk of the subject (if the nutritional risk score of the subject is greater than or equal to 3 points, the input is "1", otherwise the input is "0"). The data outputted by the output layer of the risk model for mild hepatic encephalopathy is "0" or "1". When the output is "0", it means that the subject does not have a risk of mild hepatic encephalopathy, and when the output is "1", it means that the subject has a risk of mild hepatic encephalopathy.

[0042] Figure 2The ROC curve of the risk model of mild hepatic encephalopathy in this embodiment is a receiver operating characteristic curve (ROC) drawn based on the score results of the psychological test of hepatic encephalopathy. The area under the ROC curve (AUC) of the risk model of mild hepatic encephalopathy in this embodiment is 0.818 (95% CI: 0.773-0.851), the prediction sensitivity is 72.3%, and the specificity is 76.7%. It can be seen that the risk model of mild hepatic encephalopathy in this embodiment can quickly and accurately obtain the assessment results of the patient's disease risk.

[0043] The second embodiment of the present invention relates to a device for screening risk of mild hepatic encephalopathy, comprising:

[0044] A basic information acquisition module is used to obtain the basic information of the subject;

[0045] A detection parameter acquisition module, used to obtain the detection parameters of the subject;

[0046] A nutrition risk acquisition module is used to score the nutrition risk of the subject and determine the nutrition risk status of the subject based on the scoring result;

[0047] The risk screening module is used to input the basic information, test parameters and nutritional risk status of the subject into the mild hepatic encephalopathy risk model to obtain the mild hepatic encephalopathy risk status of the subject; wherein the mild hepatic encephalopathy risk model is established based on a neural network, including an input layer, two hidden layers and an output layer.

[0048] The basic information of the subject includes the age of the subject, whether the subject has a history of diabetes, whether the subject has infection, whether the subject has renal insufficiency, and whether the subject has electrolyte disorder.

[0049] Whether the subject is infected is determined by the subject's clinical infection symptoms or test results. When the subject has clinical infection symptoms or the test results show evidence supporting infection, the subject is infected; when the subject does not have clinical infection symptoms and the test results show no evidence supporting infection, the subject is not infected.

[0050] Whether the subject has renal insufficiency is judged by the estimated glomerular filtration rate of the subject. When the estimated glomerular filtration rate of the subject is less than the renal function judgment threshold, the subject has renal insufficiency. When the estimated glomerular filtration rate of the subject is greater than or equal to the renal function judgment threshold, the subject does not have renal insufficiency.

[0051] Whether the subject has electrolyte disorder is judged by the blood sodium and blood potassium of the subject. When the blood sodium of the subject is less than the blood sodium threshold or the blood potassium of the subject is less than the blood potassium threshold, the subject has electrolyte disorder. When the blood sodium of the subject is greater than or equal to the blood sodium threshold and the blood potassium of the subject is greater than or equal to the blood potassium threshold, the subject does not have electrolyte disorder.

[0052] The test parameters of the subject include hemoglobin, total bilirubin, serum albumin, international normalized ratio, and plasma ammonia.

[0053] The nutrition score module includes:

[0054] A scoring unit, used to score the nutritional risk of the subject using the NRS2002 nutritional risk screening form;

[0055] A judging unit, used to judge whether the nutrition risk score of the subject exceeds a threshold;

[0056] The determination unit is used to determine that the subject has a nutritional risk when the nutritional risk score of the subject exceeds a threshold value, and to determine that the subject does not have a nutritional risk when the nutritional risk score of the subject does not exceed the threshold value.

[0057] The third embodiment of the present invention relates to an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the risk screening method for mild hepatic encephalopathy of the first embodiment when executing the computer program.

[0058] A fourth embodiment of the present invention relates to a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for screening the risk of mild hepatic encephalopathy of the first embodiment.

[0059] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0060] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0061] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction method, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0062] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0063] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A risk screening device for mild hepatic encephalopathy, characterized in that: The following steps are involved: A basic information acquisition module is used to obtain the basic information of the subject; A detection parameter acquisition module is used to obtain the detection parameters of the subject; A nutrition risk acquisition module is used to score the nutrition risk of the subject and determine the nutrition risk status of the subject based on the scoring result; The risk screening module is used to input the basic information, test parameters and nutritional risk status of the subject into the mild hepatic encephalopathy risk model to obtain the mild hepatic encephalopathy risk status of the subject; wherein the mild hepatic encephalopathy risk model is established based on a neural network, including an input layer, two hidden layers and an output layer.

2. The risk screening device for mild hepatic encephalopathy according to claim 1, characterized in that: The basic information of the subject includes the age of the subject, whether the subject has a history of diabetes, whether the subject has infection, whether the subject has renal insufficiency, and whether the subject has electrolyte disorder.

3. The risk screening device for mild hepatic encephalopathy according to claim 2, characterized in that: Whether the subject is infected is determined by the subject's clinical infection symptoms or test results. When the subject has clinical infection symptoms or the test results show evidence supporting infection, the subject is infected; when the subject does not have clinical infection symptoms and the test results show no evidence supporting infection, the subject is not infected.

4. The risk screening device for mild hepatic encephalopathy according to claim 2, characterized in that: Whether the subject has renal insufficiency is judged by the estimated glomerular filtration rate of the subject. When the estimated glomerular filtration rate of the subject is less than the renal function judgment threshold, the subject has renal insufficiency. When the estimated glomerular filtration rate of the subject is greater than or equal to the renal function judgment threshold, the subject does not have renal insufficiency.

5. The device for screening risk of mild hepatic encephalopathy according to claim 2, characterized in that: Whether the subject has electrolyte disorder is judged by the blood sodium and blood potassium of the subject. When the blood sodium of the subject is less than the blood sodium threshold or the blood potassium of the subject is less than the blood potassium threshold, the subject has electrolyte disorder. When the blood sodium of the subject is greater than or equal to the blood sodium threshold and the blood potassium of the subject is greater than or equal to the blood potassium threshold, the subject does not have electrolyte disorder.

6. The device for screening risk of mild hepatic encephalopathy according to claim 1, characterized in that: The test parameters of the subject include hemoglobin, total bilirubin, serum albumin, international normalized ratio, and plasma ammonia.

7. The risk screening device for mild hepatic encephalopathy according to claim 1, characterized in that: The nutrition score module includes: A scoring unit, used to score the nutritional risk of the subject using the NRS2002 nutritional risk screening form; A judging unit, used to judge whether the nutrition risk score of the subject exceeds a threshold; The determination unit is used to determine that the subject has a nutritional risk when the nutritional risk score of the subject exceeds a threshold value, and to determine that the subject does not have a nutritional risk when the nutritional risk score of the subject does not exceed the threshold value.

8. A method for screening risk of mild hepatic encephalopathy, characterized in that: The following steps are involved: Obtain basic information of the subjects; Obtaining test parameters of the subject; Score the nutritional risk of the subject and determine the nutritional risk status of the subject based on the score results; The basic information, test parameters and nutritional risk status of the subject are input into the mild hepatic encephalopathy risk model to obtain the mild hepatic encephalopathy risk status of the subject; wherein the mild hepatic encephalopathy risk model is established based on a neural network, including an input layer, two hidden layers and an output layer.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for screening risk of mild hepatic encephalopathy as claimed in claim 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for screening risk of mild hepatic encephalopathy as claimed in claim 8 are implemented.

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