22 results about "Copd patients" patented technology

The application belongs to the field of digital medicine, and particularly relates to a chronic obstructive pulmonary disease (COPD) differential system based on digital lung sound, a construction method and application thereof. The system comprises a data acquisition module, a preprocessing module, a conversion module, a data module, a data processing module, a data enhancement training module, a deep learning module, a differential module, a grading module and a display module. Digital lung sound records of candidates are collected, converted into mel spectrograms, and diagnosed by using a deep neural network. The candidates are COPD patients, healthy people, or people suffering from other lung diseases, and the disease grade of the COPD patients is given by a device carrying the differential system. The examination only needs to collect lung sounds in clinical or other places, reduces radiation damage and possible infection risk in the conventional diagnosis process, and provides a scheme for early diagnosis of COPD, and improves the diagnosis efficiency of the respiratory department, especially the COPD disease.

The application discloses a kind of application system of sitting eight-sections in COPD mechanical ventilation patient, including nurse hierarchical intervention module, man-machine synchronization module, multi-dimensional monitoring early warning module and continuity management module.The advantages of the present application: improve self-care ability of daily life, improve the critical level of patient course, reduce the hospitalization time of patient, promote the early rehabilitation of COPD mechanical ventilation patient, enhance lung function after exercise this project after discharge, avoid repeated attacks, improve the quality of life, reduce the admission rate, improve patient and family satisfaction, shorten the hospitalization time of COPD patient, reduce hospitalization expenses, reduce the readmission rate, also reduce the economic burden for society.

The application discloses a training mask for COPD patients, and relates to the technical field of medical devices.The training mask comprises a mask body, a one-way inhalation valve arranged on the left side of the mask body, an oxygen access port arranged on the right side of the mask body, a thread structure arranged on the oxygen access port, an adjustable anti-resistance exhalation module arranged at the front end of the mask body, and a resistance adjusting knob arranged on the side of the adjustable anti-resistance exhalation module.The adjustable anti-resistance exhalation module is matched with the resistance adjusting knob and a variable resistance valve sheet, so that multi-stage adjustment of exhalation resistance is realized, the training needs of different patients and different disease stages are met, and the pertinence and effectiveness of the training are improved.The training mask is integrated with a cough auxiliary triggering module, a gear shifting knob and a manual gear adjusting mechanism, so that quick switching between a training gear and a cough gear is realized, the exhalation resistance can be instantaneously reduced during the cough training, the patients can complete effective cough actions, and the airway clearance ability is improved.

The invention relates to the technical field of biological medicine, and discloses a biomarker for predicting COPD cognitive impairment and application of the biomarker. The invention finds and verifies that the specificity of stearic acid (SA) in serum and a key enzyme ELOVL6 synthesized by the stearic acid (SA) in serum in a patient with secondary cognitive impairment (CI) of chronic obstructive pulmonary disease (COPD) is improved for the first time, the level of the stearic acid (SA) and the key enzyme ELOVL6 is negatively correlated with the cognitive impairment degree, and the stearic acid (SA) and the key enzyme ELOVL6 have good prediction efficiency (AUCgt, 0.82) on the COPD-CI. On the basis, the invention provides the application of the serum SA and / or ELOVL6 as the biomarker for predicting the COPD secondary CI risk, the in-vitro diagnostic kit comprising the detection reagent of the biomarker, and the method for predicting the risk by detecting the level of the marker. The invention provides a brand-new and reliable metabolic marker tool for early warning and intervention of CI of COPD patients, and has important clinical value and transformation prospect.

The present disclosure relates to methods of treatment of asthma, COPD, Asthma-COPD Overlap Syndrome (ACOS), and chronic bronchitis, or a combination thereof, with formulations comprising (S)-3-(3-(1-methyl-2-oxo-5-(pyrazolo[1,5-a]pyridin-3-yl)-1,2-dihydro-3H-imidazo[4,5-b]pyridin-3-yl)piperidin-1-yl)-3-oxopropanenitrile.

This invention discloses an adaptive early warning and intervention system for chronic obstructive pulmonary disease (COPD), relating to the fields of telemedicine and intelligent chronic disease management. The system includes: collecting multi-source physiological and clinical data from COPD patients to obtain a multi-dimensional input dataset; extracting risk feature vectors; constructing and dynamically updating individual health profiles; inputting the risk feature vectors and clinical baseline data into an LSTM dynamic risk prediction model to output risk probabilities; performing adaptive early warning judgments based on risk probabilities and individual health profiles to output early warning levels; dynamically assembling and pushing personalized intervention plans from a structured intervention knowledge base; and continuously updating the adaptive rule base and prediction model parameters by collecting feedback data. This invention solves the technical problems of existing COPD remote management systems, such as frequent false alarms and missed alarms due to static judgment using fixed thresholds, insufficient targeting of early warning and intervention content, long response chains, and a lack of adaptive adjustment capabilities, thereby reducing the occurrence of false alarms and missed alarms.

The present disclosure relates to methods of treatment of asthma, COPD, Asthma-COPD Overlap Syndrome (ACOS), and chronic bronchitis, or a combination thereof, with formulations comprising (S)-3-(3-(1-methyl-2-oxo-5-(pyrazolo[1,5-a]pyridin-3-yl)-1,2-dihydro-3H-imidazo[4,5-b]pyridin-3-yl)piperidin-1-yl)-3-oxopropanenitrile.

The invention discloses an NPPV bidirectional switching method and system based on acute exacerbation intelligent early warning. The method comprises the steps that physiological indexes of a patient and running parameters of a breathing machine are continuously collected through a multi-source sensor; performing early warning according to the physiological indexes of the patient and the running parameters of the respirator; when the alarm signal is generated, the NPPV mode is automatically switched from low intensity to high intensity; and when the early warning release condition meets a preset condition, automatically switching the NPPV mode from high intensity to low intensity. According to the application, the re-hospitalization rate and the case fatality rate of COPD patients can be reduced, adverse reactions such as serious abdominal distension can be reduced, the problem that current NPPV treatment is not reasonable is solved, and the long-term use compliance of NPPV is remarkably improved.

The invention provides a COPD patient-oriented home exercise rehabilitation intelligent management method and system, and relates to the technical field of medical engineering and digital health. The method comprises the following steps: prompting a patient to fill in an evaluation scale; determining an undetermined rehabilitation exercise option; after confirmation information is received, taking the undetermined rehabilitation exercise options as rehabilitation exercise recommendation options; selecting a rehabilitation exercise video; playing the rehabilitation exercise video, shooting the exercise video of rehabilitation exercise of the patient, and collecting various physiological index data of the patient; determining a motion suitability index; determining a new rehabilitation exercise recommendation option; a compliance report is determined. According to the method and the device, the exercise suitability index of the patient can be determined based on the physiological index and the rehabilitation exercise video, so that a new rehabilitation exercise recommendation option is determined, and a compliance report is determined. The degree of suitability of the rehabilitation exercise for the patient is monitored in real time, personalized rehabilitation exercise is recommended for the patient, the accuracy of rehabilitation exercise recommendation is improved, and the compliance of the patient is improved.

This invention relates to the interdisciplinary application of digital health, smart healthcare, and artificial intelligence, and discloses a method and system for constructing an environmental sensitivity profile for COPD patients. The method includes: constructing a multimodal patient historical data profile dataset; reconstructing biological effects based on respiratory pathology mechanisms; constructing and training a causal feature learning network; calculating individualized environmental sensitivity; and generating clinical decision support information. Its core lies in mining multimodal longitudinal historical data of patients to construct a computational framework that deeply integrates respiratory pathology mechanisms and causal inference algorithms (a biological effect reconstruction module based on a multi-mechanism model, a causal feature learning module, and a dual machine learning module based on hypernetwork generation). This framework outputs an interpretable, individualized digital profile of environmental sensitivity, capable of quantifying a patient's pathological susceptibility to specific environmental factors (such as particulate matter), and can be combined with environmental forecasting to provide precise quantitative support for clinical decision-making.

The invention relates to an application of circular RNA (Ribonucleic Acid) in preparation of a reagent for screening chronic obstructive pulmonary disease. The circular RNA is miR-377-3p. The invention finds that miR-377-3p is up-regulated in chronic obstructive pulmonary disease patients, most of miR-377-3p is located in lung fibroblasts, and the chronic obstructive pulmonary disease can be improved by inhibiting miR-377-3p. The invention also finds that ZFP36L1 is a direct target of the miR-377-3p, and the ZFP36L1 mediates the senescence promoting activity of the miR-377-3p in the lung fibroblasts. The miR-377-3p is crucial to the attack of the chronic obstructive pulmonary disease and is expected to become a new target spot for treating the chronic obstructive pulmonary disease.

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

The invention discloses a three-chamber integrated micro-fluidic chip for simulating an airway-alveolar continuous barrier function and an application of the three-chamber integrated micro-fluidic chip in COPD (chronic obstructive pulmonary disease) drug evaluation. The chip comprises an airway chamber, a pulmonary alveolus chamber, a blood vessel chamber and a porous PET (polyethylene terephthalate) membrane, and the continuous spatial hierarchy of'airway-pulmonary alveolus-qi and blood barrier-blood vessel 'is reconstructed through a'three-chamber-in-one' bionic structure. According to the invention, optimized culture systems for the airway epithelial cells and AT2 cells from COPD patients are respectively established, airway organoid and alveolar organoid with pathological characteristics are obtained, and co-culture is realized in the chip. The chip is provided with a micro sampling port, and effluent can be collected at different time points for dynamic monitoring of inflammatory factors. By combining multi-dimensional detection such as dead and living staining, ELISA (enzyme-linked immunosorbent assay), immunofluorescence and the like, an all-dimensional evaluation system from morphology to molecules and from intracellular to extracellular is constructed. The application of erdosteine intervention verification shows that the chip can effectively simulate airway-alveolar double-part damage characteristics (including shape shrinkage, cell death increase, inflammatory factor IL-6 increase, mucus factor MUC5B high secretion and the like) of a COPD patient, and can reliably evaluate the curative effect of a medicine. The invention provides an in-vitro platform with high bionic degree and high stability for COPD mechanism research, drug screening and personalized medical treatment, and has wide industrial application prospects in the fields of respiratory disease drug research and development, toxicity evaluation and precise medicine.

The invention discloses a test method of reaction of EPHX1 genotype based COPD to NAC. The test method comprises the following steps: extracting a DNA by a phenol / chloroform method and sequencing, dividing COPD patients into slow and very slow gene activity group and a quick and normal gene activity group according to EPHX1 gene polymorphism, giving 600 mg Bid of NAC for 1 year to both groups, performing baseline measurement of pulmonary function parameters, completing SGRQ and 6MWT, measuring FVC and FEV1 at a follow-up day every 12 weeks, completingSGRQ and 6MWT in 24 and 48 weeks, and recording the number of acute exacerbationof COPD in one year. The data were statistically analyzed with SPSS. The results show that NAC is effective in the treatment of slow and very slow EPHX1 gene activityCOPD patients. The test method provided by the invention provides a solid basis for demonstrating the effect and mechanism of NAC based on pharmacogenomics in the individualized treatment of COPD.

The invention discloses a COPD patient lung function examination system based on a virtual reality technology, and relates to the technical field of medical auxiliary examination. The system comprises virtual reality hardware equipment, a self-developed respiration sensing unit, a data processing unit, a feedback module and a data management platform, wherein the virtual reality hardware equipment is electrically connected with the self-developed respiration sensing unit, the feedback module and the data management platform; the data processing unit is electrically connected with the self-research respiration sensing unit, the feedback module and the data management platform. The virtual reality hardware equipment, the self-research respiration sensing unit, the data processing unit, the feedback module and the data management platform are matched with one another, a high-simulation lung function examination virtual scene is constructed, and an immersive animation and voice guide mechanism is combined, so that the dependency threshold of the examination process on the high adaptability of a patient is effectively reduced; the workload of medical staff is relieved, the lung function detection efficiency is finally improved, and the accuracy and clinical reliability of a detection result are guaranteed.

The present application relates to medical informatics and clinical auxiliary diagnosis technical field, especially in kind of based on similarity's chronic obstructive pulmonary disease auxiliary analysis method and system, method includes obtaining the clinical diagnosis and treatment data of COPD patient to be analyzed, clinical diagnosis and treatment data at least includes lung function index, clinical symptom score and medical history information;Clinical diagnosis and treatment data are processed to the characteristics, and the disease characteristic vector is constructed;The disease characteristic vector is calculated with the historical COPD patient characteristic library, and the similar COPD patient set is filtered;Based on the clinical outcome information of similar COPD patient set, COPD auxiliary diagnosis analysis result is generated, and is used to assist doctors to carry out disease assessment and risk prompt.The present application can comprehensively reflect the individual difference of COPD, improve the individualization level and clinical interpretability of disease assessment, and be applicable to the outpatient, hospitalization and follow-up management scene of COPD.

The application provides a home exercise rehabilitation intelligent management method and system for COPD patients, and relates to the fields of medical engineering and digital health technology.The method comprises the following steps: prompting the patient to fill in an evaluation scale; determining a pending rehabilitation exercise option; after receiving confirmation information, taking the pending rehabilitation exercise option as a rehabilitation exercise recommended option; selecting a rehabilitation exercise video; playing the rehabilitation exercise video, shooting an exercise video of the patient performing the rehabilitation exercise, collecting various physiological index data of the patient; determining an exercise suitability index; determining a new rehabilitation exercise recommended option; and determining a compliance report.According to the application, the exercise suitability index of the patient can be determined based on the physiological index and the rehabilitation exercise video, and then the new rehabilitation exercise recommended option and the compliance report are determined.The real-time monitoring of the suitability of the rehabilitation exercise for the patient can recommend personalized rehabilitation exercise for the patient, improve the accuracy of the rehabilitation exercise recommendation, and improve the compliance of the patient.

The invention discloses a circular RNA (Ribonucleic Acid) capable of being used as a potential therapeutic target for chronic obstructive pulmonary disease, and relates to the technical field of biological medicines, tests prove that circular RNA circFCHO2 is remarkably and highly expressed in COPD patient tissues and mouse COPD models, so that circFCHO2 can be used as a basis for clinical diagnosis of COPD. According to the invention, circFCHO2 is further utilized to construct an adeno-associated virus AAV knock-down vector, and in-vivo verification finds that circFCHO2 can significantly improve lung function, emphysema and airway remodeling related indexes of a mouse COPD model. Therefore, circFCHO2 can be used as a novel target and a potential drug for clinical treatment of COPD, a new direction is provided for research and development of drugs for treatment of COPD, and the circFCHO2 has clinical transformation potential.

This invention discloses the application of the BMP4 gene and its regulatory products in the preparation of products for the prevention and treatment of COPD, belonging to the field of biomedical technology. This invention found that BMP4 expression is reduced in the lung tissue of COPD patients; animal experiments demonstrated that after CS exposure, BMP4 expression... + / ‑ Mice showed decreased body weight, significantly impaired lung function, more pronounced emphysema and inflammatory infiltration, a significantly increased mean alveolar intercept, and a significantly increased number of inflammatory cells, predominantly neutrophils, in bronchoalveolar lavage fluid. CS exposure combined with airway infusion of AAV9-BMP4 revealed that airway infusion of AAV9-BMP4 (1×10⁻⁶) significantly reduced lung function. 11 PFU / mouse significantly improved decreased lung function, emphysema, inflammatory infiltration, increased mean alveolar intercept, and increased number of inflammatory cells in bronchoalveolar lavage fluid in mice after CS exposure. This suggests that BMP4 may be a potential target for COPD treatment and could be applied to the development of new drugs and technologies for COPD.

The application discloses a chronic obstructive pulmonary disease related pulmonary hypertension (COPD-PH) specific metabolic marker combination based on metabolomics and machine learning screening, and relates to the technical field of biological medicine.The application first discovers specific metabolic characteristics of COPD-PH patients.Plasma samples of COPD-PH patients, COPD patients and healthy controls are subjected to non-targeted metabolomics analysis, and 163 differential metabolites are identified, then three machine learning algorithms, RF, SVM and LASSO, are comprehensively analyzed, and five key metabolites, ornithine, histidine, biotin, nicotinamide and homocysteine, are screened out.In a multi-center verification study, the five metabolite combination also exhibits excellent diagnostic efficiency [AUC = 0.814], which is significantly better than traditional diagnostic indexes.The application not only provides a new tool for non-invasive diagnosis of COPD-PH, but also further reveals the metabolic mechanism of disease occurrence and development.

This invention discloses a screening system for COPD patients in respiratory medicine, specifically in the field of computer-aided diagnosis, to address the technical problems of low screening efficiency, low patient cooperation, and difficulty in large-scale promotion at the grassroots level in existing screening methods. The system acquires medical records of the target population containing drug delivery and disease diagnosis codes to construct standardized patient medical event sequences; identifies characteristic medication and diagnostic patterns prior to COPD diagnosis using sequence pattern mining technology; constructs a medical knowledge graph using these patterns; learns feature embedding vectors representing COPD medical trajectories through graph neural networks to establish high-risk digital profiles; inputs the medical sequences of the individuals to be screened into a feature extraction model trained on the same knowledge graph; and generates individualized risk probability prediction values ​​by calculating the matching degree between the medical sequence and the digital profile; automatically generates screening result reports, achieving efficient and non-invasive early risk screening.

The invention discloses a COPD image diagnosis phenotype automatic classification method based on an AI technology. The COPD image diagnosis phenotype automatic classification method comprises the following steps of 1, obtaining HRCT image data of a COPD patient; 2, performing image phenotype classification evaluation on the HRCT image of the COPD patient to form a phenotype classification gold standard; step 3, carrying out normalization and denoising preprocessing on the HRCT image; 4, performing feature extraction on the preprocessed HRCT image; step 5, a ResidualAttention Network phenotype classification model is established, and step 5, a ResidualAttention Network phenotype classification model is established; and step 6, performing performance evaluation on the Residual Attention Network phenotype classification model, and outputting a classification result. According to the method, the multi-classification model is constructed through the HRCT data, the COPD image is divided into different image phenotypes, accurate classification of COPD is facilitated, more efficient and rapid diagnosis is realized, and a doctor is assisted in performing a diagnosis and treatment plan.