39 results about "Exacerbation" patented technology

The invention discloses a COPD-FE risk prediction method based on disease and symptom combination, and is applied to the technical field of chronic obstructive pulmonary disease risk prediction. Comprising the following steps: acquiring chronic obstructive pulmonary frequent acute exacerbation influence factor data of a patient; the influence factors are screened through LASSO regression and an improved Boruta algorithm respectively; the LASSO independent influence factors and the Boruta independent influence factors are combined in different modes, a Logistic regression model and an XGBoost model are trained, and a plurality of COPD-FE risk prediction models are obtained; and evaluating the performance of all the COPD-FE risk prediction models, and selecting the COPD-FE risk prediction model meeting the requirement to predict the COPD-FE risk. According to the method, clinical data of patients are collected, a risk prediction model is constructed in combination with a feature selection method and machine learning, and an optimal model is screened out through comprehensive evaluation.

The invention provides a follow-up visit consultation system for chronic pain patients, and relates to the technical field of intelligent medical treatment, and the system comprises a data collection unit which is used for obtaining subjective pain description data, real-time physiological monitoring data and historical diagnosis and treatment data of a patient; the prediction analysis unit is used for performing pain deterioration risk prediction based on the multi-source data and an artificial intelligence model, and outputting a prediction result containing a risk level and individualized pathological features; and the dynamic intervention unit is used for generating dynamic treatment suggestions according to the prediction result, pushing the dynamic treatment suggestions to the doctor and the patient, and receiving execution feedback data of the patient so as to perform closed-loop optimization on the treatment strategy. According to the technical scheme, the subjective pain description, the real-time physiological monitoring data and the historical diagnosis and treatment records of the patient are obtained at the same time, the integrity of the data is improved through the comprehensive collection mode of multi-source data, the accuracy and timeliness of information are ensured, and the problems of subjective deviation and inaccuracy caused by the fact that follow-up visit depends on memory of the patient are solved.

The invention provides a chronic respiratory system disease risk early warning method and device based on artificial intelligence and a medium. The method comprises the following steps: firstly, acquiring physiological monitoring information of wearable equipment of a patient; inputting the physiological monitoring information into the risk prediction model to obtain a risk early warning result; wherein the risk prediction model is established according to patient medical record information, follow-up visit information and historical physiological monitoring information; the risk prediction model is a Transform-LSTM (Long Short Term Memory) double-branch integrated model. According to the method, physiological monitoring information collected by wearable equipment in real time is input into a Transform-LSTM double-branch integrated model constructed on the basis of patient medical record, follow-up visit and historical physiological monitoring multi-source information, so that a long-distance dependency relationship of multi-modal data is captured by means of a Transform branch to identify a potential risk trend in a stable period; and the time sequence dynamic characteristics of physiological monitoring information are captured through an LSTM branch to perceive short-term signal mutation in an acute exacerbation period, so that accurate early warning of the whole course risk of the chronic respiratory system disease is realized.

Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality worldwide. Acute exacerbation of COPD (AE-COPD) in patients are mostly due to respiratory infection and are associated with an inexorable decline in lung function, enhanced oedema as well as airway and systemic inflammation. Previous results show that treatment with anti-IL-20Rb blocking antibodies increased the bacterial clearance in control mice infected by S. pneumoniae and protected CS-exposed mice from bacterial infection, by decreasing the bacterial burden and the inflammatory infiltrate. Therefore there is an interest for generating monoclonal antibodies specific for IL-20Rb with a neutralizing activity for their use in the treatment of AE-COPD. The present invention fulfills this need by providing antibodies having specificity for IL-20Rb.

This invention provides a method and system for precise follow-up of chronic diseases based on big data, relating to the field of chronic disease follow-up technology. The method includes: acquiring discharge diagnosis and treatment data and discharge vital sign data; acquiring home vital sign data; determining measured vital sign recovery data; inputting the discharge diagnosis and treatment data and the discharge vital sign data into a trained vital sign recovery prediction model to obtain predicted vital sign recovery data for multiple patients at multiple home times; determining the highest recovery coefficient based on the measured vital sign recovery data and the predicted vital sign recovery data; acquiring the ages of multiple patients, as well as the number of acute exacerbations and hospitalization frequency within one year; determining a risk coefficient based on the age, the number of acute exacerbations, and the hospitalization frequency; and determining the follow-up order and follow-up frequency. According to this invention, personalized follow-up plans can be formulated based on the highest recovery coefficient and the risk coefficient, improving the accuracy and effectiveness of follow-up and reducing the waste of medical resources.

The present application relates to the technical field of health care, in particular to an intelligent early warning system for dynamic exacerbation of chronic obstructive pulmonary disease, which is used to solve the technical problem of inaccurate assessment of lung ventilation capacity of users in the prior art. The system comprises: a data acquisition unit for acquiring lung function time series data and multi-dimensional physiological time series data of a target user in an observation period; the observation period comprises a plurality of consecutive days; a processing unit for determining suspected abnormal days according to the lung function time series data, determining the deviation degree of the multi-dimensional physiological time series data of the suspected abnormal days and the multi-dimensional physiological time series data of the reference days and the similarity of the different dimensional physiological time series data deviation degrees, determining the abnormal days from the suspected abnormal days based on the deviation degree and the similarity, and determining the dynamic exacerbation risk level of the target user's chronic obstructive pulmonary disease based on the abnormal days; and performing risk warning based on the dynamic exacerbation risk level of the target user's chronic obstructive pulmonary disease.

The invention discloses an intelligent early warning system for acute exacerbation of COPD home NPPV, which belongs to the technical field of medical treatment and comprises a real-time multi-dimensional physiological data time sequence acquisition module, a COPD acute exacerbation prediction model and an early warning module. The real-time multi-dimensional physiological data time sequence acquisition module is used for acquiring a real-time multi-dimensional physiological data time sequence of a patient; the COPD acute exacerbation prediction model is used for outputting the probability that the patient has COPD acute exacerbation in the future according to the input real-time multi-dimensional physiological data time sequence; and the early warning module is used for performing early warning when the probability of acute exacerbation of COPD of the patient in the future is greater than a preset threshold value. According to the method, the prediction precision of whether COPD acute exacerbation occurs in the future can be improved, and early discovery and early treatment are realized.

Agents, kits, and methods that utilize oxygenation to treat Inflammatory Bowel Disease (IBD) and / or provide prophylaxis against exacerbation of IBD are provided. In several embodiments, the agents, kits, and methods according to several embodiments generate in, or carry to, oxygen in the intestinal lumen to treat IBD and provide prophylaxis against exacerbation of IBD, including those caused by the presence of anaerobic bacteria in the intestine. The agents, kits, and methods provided herein generate an aerobic environment within the intestine to alleviate intestinal inflammation.

The present invention relates to the use of a family of compounds, the compounds of formula (I), for use thereof in preventing and / or treating autoimmune diseases, in particular systemic lupus erythematosus (SLE), in a subject in need thereof. In particular, the invention relates to the prevention and / or treatment of organic lesions and relapses, exacerbation or flare-ups, and adverse consequences for the health in a subject with systemic lupus erythematosus (SLE).

The present invention relates to compositions, methods and kits for the treatment of respiratory disease. In particular, the compositions, methods and kits are particularly useful, but not limited to, the treatment or prevention of exacerbations of asthma and chronic obstructive pulmonary disease. The present invention provides a method of treating or preventing a respiratory disease in a subject in need thereof, the method comprising administering to the subject a therapeutically effective amount of an inhibitor of casein kinase 1, thereby treating or preventing a respiratory disease in a subject. The present invention also provides a method of treating or preventing a respiratory disease in a subject in need thereof, the method comprising administering to the subject a therapeutically effective amount of an inhibitor of ALK5, thereby treating or preventing a respiratory disease in a subject, wherein the inhibitor is administered directly to the airway and / or lungs. The present invention also provides a method of treating or preventing a condition of the airway or lung involving fibrosis in a subject in need thereof, the method comprising administering to the subject a therapeutically effective amount of an inhibitor of casein kinase 1 or an inhibitor of ALK5, thereby treating or preventing a condition of the airway or lung involving fibrosis in a subject.

The invention discloses a device and equipment for predicting the death rate of a patient with chronic obstructive pulmonary disease and a medium, and relates to the technical field of clinical medicine application. The device comprises an acquisition module and an input module. The acquisition module is used for acquiring physical sign parameters of a patient; the physical sign parameters at least comprise age, a body mass index, the percentage of FEV1 accounting for a predicted value, an mMRC score and the occurrence frequency of first-level acute exacerbation in a preset follow-up visit period; the input module is used for inputting the physical sign parameters into the chronic obstructive pulmonary disease patient death rate prediction model so as to obtain the death rate corresponding to the patient through the chronic obstructive pulmonary disease patient death rate prediction model; the model for predicting the death rate of the chronic obstructive pulmonary disease patient is a model generated according to the death rates corresponding to the patients with different physical sign parameters. According to the scheme, the model for predicting the death rate of the patient with chronic obstructive pulmonary disease is constructed on the basis of multiple predictive factors, and more comprehensive evaluation can be provided for prognosis of the chronic obstructive pulmonary disease compared with a single predictive factor; meanwhile, the physical sign parameters of the patient are simply and quickly collected, and the prediction efficiency is improved.

To provide a pharmaceutical composition that improves exacerbation of an inflammatory reaction due to a chronic hypoxic condition resulting from reduced circulatory or respiratory function, or from anemia.SOLUTION: It has been found that pyridoxal synthase Pyridoxamine-5'-phosphate oxidase (PNPO) functions as a novel oxygen-sensing mechanism. A pharmaceutical composition containing pyridoxal or pyridoxal phosphate as an active ingredient acts as a pharmaceutical composition for improving exacerbation of an inflammatory reaction due to a chronic hypoxic condition.SELECTED DRAWING: Figure 10

The invention discloses an establishment method and application of an animal model of a mental stress exacerbation metabolic disease, and belongs to the technical field of biomedicine. The method comprises the following steps: selecting SPF-level C57BL / 6J mice, randomly grouping the mice, adaptively feeding the mice for 7 days, and then periodically and cyclically modeling the mice for four cycles in total. Each cycle comprises two weeks of 60% high fat diet feeding and one week of common maintenance feed diet; 7-day chronic social failure stress modeling is carried out during a common feed diet maintaining period. According to the method disclosed by the invention, the mouse model capable of effectively simulating clinical mental stress exacerbation glycolipid metabolism disorder is constructed, and the blank of a model for inducing glycolipid metabolism disorder by combining mental stress and dietary factors is filled. The mouse model provided by the invention is helpful for promoting the pathogenesis of metabolic diseases and researching potential therapeutic targets.

Provided are a monoclonal antibody molecule or a derivative thereof against corisin and a pharmaceutical composition containing the same for ameliorating acute lung injury and acute exacerbation of pulmonary fibrosis. The pharmaceutical composition of the present invention contains a monoclonal antibody molecule or a derivative thereof against corisin, which is a peptide conserved in diverse Staphylococci, such as Staphylococcus nepalensis.

Provided are a computer program, an information processing method, an information processing device, an information processing system, and a method for generating a trained model for evaluating the exacerbation of heart failure more accurately than before.　This computer program causes a computer to execute processing comprising: acquiring first biological information related to hemodynamics of a patient at a first time point and second biological information related to a compensatory mechanism associated with heart failure of the patient at a second time point different from the first time point; and deriving an index related to the progression level of exacerbation of heart failure of the patient at an evaluation time point later than the first time point and the second time point on the basis of the first biological information and the second biological information acquired.

FIELD: pediatrics and pulmonology.SUBSTANCE: used to predict the risk of severe bronchial asthma in children. Anamnesis is collected, blood is taken, and the child's blood is tested in a laboratory. From the anamnesis, the duration of the disease in years and the number of exacerbations over the current 12 months in points are specified. The peak expiratory flow rate is measured using a peak flow meter, %. The concentration of connexin 43 (CX43), ng / ml, is determined in the child’s blood serum at the time of inclusion in the study. The prognosis for the risk of severe bronchial asthma in children P is calculated using the stated formula. If the P value is 0.52 or higher, a high risk of severe bronchial asthma is predicted.EFFECT: method provides the possibility of increasing the accuracy and reliability of the prognosis of the severity of bronchial asthma in children by taking into account the declared clinical symptoms and risk factors for bronchial asthma in children and adolescents of both sexes who do not have signs of a severe course of the disease at the time of examination.1 cl, 4 ex

The present disclosure provides a method of treating eosinophilic COPD and / or eosinophilic inflammatory responses of eosinophilic COPD in a subject in need thereof. The method comprises orally administering to the subject a therapeutically effective amount of dexpramipexole, or a pharmaceutically acceptable salt thereof. The treating eosinophilic COPD can comprise reducing the rate of COPD exacerbation, reducing a mucus plug score, reducing the rate of hospitalizations due to exacerbations, reducing the rate of oral / parenteral steroid and / or antibiotic use for treatment of COPD, changing the level of one or more biomarkers associated with eosinophilic chronic obstructive pulmonary disorder (COPD), lung function decline, or any combination thereof.

A method for testing a diseased state of vasculitis and a method for testing an exacerbation risk of COVID-19, the method including: detecting or quantifying, in a blood sample collected from a subject, (1) a No. 1 APOA2-like protein that causes an antigen-antibody reaction with a single chain variable region fragment consisting of an amino acid sequence set forth in SEQ ID NO: 1 and has a molecular weight of 23 to 25 kDa, and / or (2) a No. 2 APOA2-like protein that causes an antigen-antibody reaction with a single chain variable region fragment consisting of an amino acid sequence set forth in SEQ ID NO: 1 and has a molecular weight of 16 to 20 kDa.

The invention discloses an F-ILD acute exacerbation event prediction method and system based on quantitative image analysis. The method comprises the steps of obtaining a lung computed tomography image, lung function parameters and clinical data of a patient; carrying out quantitative analysis on the computed tomography image of the lung of the patient by adopting computer-aided quantitative analysis software; lASSO regression analysis is carried out through an R language to screen out independent influence factors of acute exacerbation events, and an exacerbation event prediction model is constructed based on the independent influence factors; and inputting to-be-predicted patient data into the exacerbation event prediction model to obtain the occurrence probability of the acute exacerbation event of the patient. The method provided by the invention is helpful for evaluating the occurrence probability of acute exacerbation of patients with fibrotic interstitial lung diseases, so that close follow-up visit to the patients of the type clinically is improved, acute exacerbation is prevented, the patients are managed in time, and deterioration of the disease of high-risk patients is delayed.

The present disclosure relates to a method and device for predicting acute exacerbation, an electronic device and a storage medium. The method for predicting acute exacerbation includes: obtaining the number of acute exacerbations corresponding to a plurality of patients at a first time and a second time, clinical text data and / or lung images at the first time; determining training labels according to the number of acute exacerbations corresponding to the first time and the second time; training a preset classifier using the clinical text data and / or the lung images and the corresponding training labels; based on the trained preset classifier, using the clinical text data and / or lung images of the patient to be predicted at the first time, completing the prediction of the acute exacerbation of the patient to be predicted at the second time. The embodiment of the present disclosure can realize the prediction of acute exacerbation.

To provide further improved therapeutic compositions for those with infection-related exacerbations, such as chronic obstructive pulmonary disease (COPD) and non-cystic fibrosis bronchiectasis (NCFB), to prevent or treat acute exacerbations.SOLUTION: The present invention provides a composition for preventing or treating acute exacerbations in chronic lung diseases, such as COPD and NCFB, by administration of polyclonal immunoglobulin to the respiratory tract, in particular by direct application of an aerosolized composition comprising polyclonal immunoglobulin.SELECTED DRAWING: None

This invention provides the application of β2-microglobulin in the preparation of products for diagnosing and / or prognostically assessing acute exacerbations of COPD, relating to the field of biotechnology. This invention detects the level of β2-microglobulin in plasma samples of subjects, showing that the level of β2-microglobulin in plasma samples from patients experiencing acute exacerbations of COPD is significantly upregulated compared to healthy controls. This invention also follows up patients with acute exacerbations of COPD for one year after discharge, statistically analyzing relapse rates and survival. Patients are divided into high-value and low-value groups based on their β2-microglobulin levels at enrollment. Multivariate analysis shows that low concentrations of β2-microglobulin are an independent risk factor for recurrent acute exacerbations in patients with end-stage COPD. The experimental results of this invention suggest that β2-microglobulin has diagnostic and prognostic value in acute exacerbations of COPD.

Disclosed herein are antigen binding proteins, e.g. an antibody, which bind to IL-5, for use in the treatment of asthma, wherein the rate of exacerbations is reduced.

The invention provides a graded diagnosis and acute exacerbation prediction method for chronic obstructive pulmonary disease based on machine learning. The method comprises the following steps: acquiring lung function measurement data, clinical information, laboratory detection results, CT images, metabolism analysis data and emergency follow-up visit records of a patient; performing image segmentation of a lung lobe region on the CT image by using a convolutional neural network; carrying out statistical analysis on other data except the CT image after standardization processing; fusing the index data related to the severity of the chronic obstructive pulmonary disease and the image features related to the severity of the chronic obstructive pulmonary disease to obtain a prediction variable set; dividing the prediction variable set into a training set, a verification set and a test set; inputting the training set into a machine learning model for training, and inputting the verification set into the trained model for optimization; and inputting the test set into the final optimized model to obtain a prediction result of the grading diagnosis index of the chronic obstructive pulmonary disease patient and a prediction result of whether an acute exacerbation trend exists or not.

Disclosed herein are methods and nanoparticles suitable for use in reducing exacerbations in COPD patients.SOLUTION: The methods and compositions advantageously reduce the incidence of hospitalization of COPD patients that occurs in response to an environmental challenge, such as exposure to or infection by RSV. Also disclosed are dosages, formulations, and methods for preparing the vaccines and nanoparticles.SELECTED DRAWING: Figure 1

A method of treating an episode of acute exacerbation of schizophrenia by intramuscular administration of a long-acting injectable depot composition containing risperidone is provided. The method provides a substantial reduction in PANSS (both positive and negative scales) and CGI-S scores within about eight days after administration of the composition and for up to at least four weeks. The method is used to treat a subject suffering a first-time episode of or a relapse of severe to moderate symptoms associated with schizophrenia. The method does not require loading doses of risperidone in the depot composition and does not require supplementation with oral risperidone after administration of the depot composition.

The application discloses a kind of construction methods of combined induction aggravation asthma animal model.The method includes: abdominal cavity injection egg white protein or house dust mite extract is sensitized;Allergen is inhaled by atomization and is exposed to airway;In aggravation stage, give pseudomonas aeruginosa, lung fumagine or respiratory syncytial virus and expose to 500 μg / m 3 PM2.5 aerosol;Subsequently, lung tissue and bronchoalveolar lavage fluid are detected.The model shows that airway resistance is significantly enhanced and continues, the rate of mucus plug formation is greater than 50%, smooth muscle is significantly thickened, accompanied by eosinophil and neutrophil infiltration and high expression of various inflammatory factors.The model of the application has good stability, strong repeatability, can truly simulate clinical asthma acute exacerbation and steroid-insensitive characteristics, and provides a platform for asthma mechanism research and new drug screening.

Provided herein are methods of treating acute exacerbations of asthma and chronic obstructive pulmonary disease (COPD) comprising administering to the patient an anti-interleukin- 5 receptor alpha (IL-5Rα) antibody or an antigen-binding fragment thereof such as benralizumab.

Rheumatoid arthritis (RA) is the most common form of inflammatory rheumatism involving small joints which are the seat for swelling and pain with structural damage, responsible for functional disabilities if no treatment is proposed. The inventors show that circulating MAIT cells were reduced and exhibited an activated and anti-apoptotic phenotype in RA patients compared to healthy controls. MAIT cell levels were also found to be increased in the synovial fluid as compared with the peripheral blood, suggesting that circulating MAIT cell deficiency is due to the migration of MAIT cells into the joint. Severity of arthritis induced by mBSA was reduced in mice depleted in MAIT cells. This data suggest that MAIT cells contribute to exacerbation of arthritis. Thus the present invention relates to the use of an agent capable of inhibiting the activation of MAIT cells for the treatment of rheumatoid arthritis

In the present invention, a photoplethysmography signal corresponding to the pulse of a subject is acquired in time series by a sensor (S101). On the basis of a pulse waveform represented by the time-series photoplethysmography signal, a feature amount including at least the interval, amplitude, and baseline of the pulse waveform is extracted for each beat (S104). On the basis of the pulse waveform, a respiratory period corresponding to each respiration of the subject is identified (S107). The respiratory period is a period including a plurality of consecutive beats. From the pulse waveform, a variation amount of the interval, a variation amount of the amplitude, and a variation amount of the baseline in an assessment segment that has been set corresponding to one or more of consecutive respiratory periods are calculated (S108). On the basis of the variation amount of the interval, the variation amount of the amplitude, and the variation amount of the baseline in the assessment segment, an exacerbation severity, which numerically represents the degree of exacerbation of a respiratory disease of the subject, is calculated (S109, S110). Thus, the degree of exacerbation of the respiratory disease of the subject is assessed.