19 results about "Exacerbation" patented technology

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.

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.

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).

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.

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

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

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.

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.

What are provided are: a prophylactic or therapeutic agent against relapse or recurrence of cancer due to cells including dormant cancer stem cells during chemotherapy, the prophylactic or therapeutic agent including a YAP inhibitor as an active component; and a screening method including a step (a) of allowing a chemotherapeutic agent to act on cancer organoids, resulting in death of most of the cancer organoids, a step (b) of further incubating the cancer organoids, resulting in start of proliferation of cells including dormant cancer stem cells present in the cancer organoids, and a step (c) of evaluating the proliferation of the cells including the dormant cancer stem cells, in which the step (a) or (b) is carried out in the presence of a test substance, and the fact that the proliferation of the cells including the dormant cancer stem cells is inhibited compared to that in the absence of the test substance indicates that the test substance is a prophylactic or therapeutic agent against relapse or recurrence of cancer due to cells including dormant cancer stem cells during chemotherapy.

The invention discloses a severe asthma treatment response and deterioration risk personalized early warning system, and the system comprises a data collection module which is used for carrying out the real-time monitoring of FeNO through a portable FeNO monitoring device, and uploading the data to a cloud server in real time through a matched mobile application; the trend identification module is used for smoothing the original FeNO data which are collected by the data collection module and are full of noise by using an LOESS algorithm, and matching the smoothed trajectory with a standard trajectory pattern library; the model construction module is used for learning FeNO dynamic characteristics of patients through Kalman filtering and constructing a dynamic prediction model for each patient; and the dynamic prediction module is used for predicting the normal fluctuation range of the FeNO at the next time point by using the trained dynamic prediction model, identifying an abnormal event and triggering early warning. Abnormal changes of the patient can be captured in time, the risk of disease deterioration can be recognized in advance, and precious time is won for clinical intervention.

The present invention relates to the compound of Formula 1 and STING antagonists, for example, systemic lupus erythematosus (SLE), (monogeneic and digeneic) interferon disorders (including STING-associated vascular disorders that develop in infancy (SAVI), Eicardi-Goutier syndrome (AGS), COPA syndrome, and familial chilblain lupus), type 1 interferon disorders with mutations in DNASE2 or ATAD3A genes, age-related macular degeneration (AMD), retinopathy, glaucoma, amyotrophic lateral sclerosis (ALS), diabetes mellitus, obesity, and inflammatory bowel disease. This relates to the use of these as STING antagonists for the treatment of diseases selected from the group consisting of intestinal diseases (IBD), chronic obstructive pulmonary disease (COPD), Bloom syndrome, Sjögren's syndrome, Parkinson's disease, heart failure and cancer, systemic sclerosis (SSc), dermatomyositis, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), acute exacerbation of chronic liver failure (ACLF), interstitial lung disease (ILD), idiopathic pulmonary fibrosis (IPF), age-related / muscle disorders, sepsis, heart failure, rheumatoid arthritis and osteoarthritis. JPEG2026510538000418.jpg45150

The application provides a respiratory failure acute exacerbation prediction method and system based on multi-data fusion analysis and deep learning, comprising: updating the disease fluctuation variance according to local correction to output, adopting a support vector machine to classify the disease fluctuation variance level to determine a prediction step selection value; after obtaining the prediction step selection value, fusing historical cache features, if the prediction step selection value is a short step, adjusting the cache window setting to expand to a twelve-hour range to obtain fused window data; calculating and updating the data dimension for the fused window data, judging the key node trigger timing by random forest evaluation of the degree of multi-source information fusion; adopting a conflict resolution sequence to reset the cache window, obtaining the expanded window data to judge whether the window expansion requirement meets the global self-adaptive requirement to obtain the final prediction result; verifying the matching degree of the disease fluctuation variance and the prediction step selection through the final prediction result, and determining the confirmation signal that the overall execution conflict has been resolved.

To assess the degree of exacerbation of the subject's respiratory disease. [Solution] A photoplethysmography signal corresponding to the subject's pulse is acquired in time series by a sensor (S101). Based on the pulse waveform represented by the time-series photoplethysmography signal, feature quantities including at least the interval, amplitude, and baseline of the pulse waveform are extracted for each beat (S104). Based on the pulse waveform, the respiratory period corresponding to each breath of the subject is identified (S107). The respiratory period is a period that includes multiple consecutive beats. From the pulse waveform, the amount of variation in interval, the amount of variation in amplitude, and the amount of variation in baseline are calculated in an evaluation interval set corresponding to one or more consecutive respiratory periods (S108). Based on the amount of variation in interval, the amount of variation in amplitude, and the amount of variation in baseline in the evaluation interval, the degree of exacerbation, which numerically represents the degree of exacerbation of the subject's respiratory disease, is calculated (S109, S110).

The invention relates to the technical field of pneumoconiosis medical management and multi-modal data processing, discloses a pneumoconiosis respiratory function management system and method based on multi-modal data fusion, and aims to solve the problems that existing pneumoconiosis respiratory function evaluation is low in accuracy and acute exacerbation risk early warning is delayed. The system comprises a multi-source data acquisition module, a multi-modal data fusion module and an intelligent analysis and evaluation module, wherein the multi-source data acquisition module acquires medical detection, physical signs, iconography, living habits and medication data of a patient and performs standardization processing; the multi-modal data fusion module adopts a data layer-feature layer-decision layer three-level progressive architecture to generate a fusion feature set; and the intelligent analysis and evaluation module realizes respiratory function grading, acute exacerbation risk early warning and abnormal data tracing based on the fusion features. According to the method, efficient fusion of multi-source data is realized, the management accuracy and timeliness are improved, support is provided for clinical intervention, and the clinical application value is remarkable.

The present invention relates to the use of compound I, namely mebeverine and its derivatives, for the prevention and / or treatment of autoimmune diseases, particularly systemic lupus erythematosus (SLE), in a subject in need. Specifically, the invention relates to the prevention and / or treatment of organ damage, flare-ups, exacerbation or worsening of the disease, or any adverse health consequences of SLE in a subject with systemic lupus erythematosus (SLE).