775 results about "Sepsis" patented technology

The invention relates to the technical field of intelligent medical treatment, and discloses an AI-based severe patient sepsis early warning method and system. According to the method, a multi-organ interaction mechanism is deeply analyzed by dynamically constructing an organ-level causal network, and early-stage accurate early warning of sepsis is realized: high-frequency physiological waveforms, asynchronous laboratory indexes and treatment intervention data are fused, and the capture ability of microcirculation failure and autonomic nerve decline is improved; the early warning threshold value is dynamically adjusted based on the treatment coverage degree, and the delay and false alarm defects of a fixed threshold value mechanism are effectively overcome; a pathogen targeted therapy map and an organ function support scheme are automatically generated by a graded triggered clinical action chain, and the clinical decision response time is shortened; according to the method, the risk of missed diagnosis is reduced while the early warning sensitivity is improved, and an earlier and more reliable intervention window is provided for critical patients.

The invention provides a metal polyphenol nanoparticle, a preparation method thereof and an application of the metal polyphenol nanoparticle in preparation of a medicine for treating acute lung injury, the metal polyphenol nanoparticle is formed by self-assembly of metal ions and polyphenol, the metal ions are selected from Mg < 2 + >, Zn < 2 + >, Mn < 2 + > or Cu < 2 + >, and the polyphenol is selected from Mg < 2 + >, Zn < 2 + >, Mn < 2 + > or Cu < 2 + >. The polyphenol is selected from epigallocatechin gallate (EGCG), caffeic acid (CA), chlorogenic acid (CGA), gallic acid (GA) and luteolin (LUT). The metal polyphenol nanoparticles are used for preparing a medicine for treating acute lung injury induced by sepsis, pneumonia, serious trauma or inhalation injury, and the medicine further comprises a pharmaceutically acceptable carrier. The metal polyphenol nanoparticles provided by the invention are simple in preparation process and high in biological safety, polyphenol and metal ions synergistically enhance the anti-inflammatory and antioxidant activity, and the metal polyphenol nanoparticles are superior to the single use of polyphenol or metal ions.

The invention discloses an ICU sepsis two-stage early prediction method and device and a storage medium, and the method comprises the steps: continuously collecting a clinical data set after a patient enters an ICU, and carrying out the feature extraction, and obtaining a prediction feature vector; based on the predicted feature vector corresponding to the clinical data set at the current observation moment, determining whether the patient is a non-sepsis sample by using a preset classification model; and if the patient is not determined as a non-sepsis sample by the classification model, predicting whether the patient has a sepsis infection risk in a future preset time period or not by using a preset prediction model according to the current observation moment and the prediction feature vector corresponding to the clinical data set in the previous set time. According to the application, a two-stage mode is adopted, patients are subjected to layered screening, and samples which do not obviously belong to sepsis are excluded; and for the samples which are not excluded, more accurate sepsis risk prediction is carried out by using the prediction model in combination with the prediction feature vectors corresponding to the clinical data of the plurality of time periods, so that the prediction accuracy is improved.

The invention specifically relates to a clinical deterioration risk prediction and early warning system and method based on machine learning, and relates to the technical field of medical artificial intelligence and clinical informatics, and the method comprises the steps: obtaining multi-dimensional time series data in real time; constructing a dynamic feature engineering vector; machine learning risk prediction; judging a risk threshold value and triggering early warning; and interpretation and suggestion generation driven by the large language model. According to the method, multi-dimensional time sequence data is continuously acquired in real time, multi-sliding window statistical features and standardized clinical deterioration scores are extracted in combination with dynamic feature engineering, and accurate quantitative risk prediction of multiple disease deterioration types such as sepsis and respiratory failure is realized by means of machine learning models which are specifically trained by XGBoost, LSTM and the like. The problem that traditional early warning depends on manual judgment and is high in hysteresis is effectively solved; medical staff can be helped to quickly grasp the core inducement of disease deterioration, and a standardized and landing action scheme is provided.

The invention discloses a sepsis-related acute kidney injury intelligent prediction system and a hierarchical management method, and the system comprises a multi-modal data collection module which synchronously collects an ultrasound contrast video, a urine biomarker and hemodynamic parameters in real time; the spatio-temporal feature extraction module is used for extracting multi-modal spatio-temporal features; modeling a dynamic interaction effect of heart and kidney nodes through a dynamic organ interaction graph network; the self-supervised pre-training module is used for improving the generalization of the model through comparative learning; the dynamic risk prediction module outputs a risk probability curve in the next 24 hours; the hierarchical decision management module is used for generating personalized strategies of liquid management, vasoactive drug adjustment and kidney replacement treatment opportunity; and the interpretability module is used for analyzing the key early warning characteristics based on the SHAP value. According to the method, the problems of deficiency of organ interaction modeling, poor generalization of small samples, stiffness of static decision and the like are solved, and the early warning and precise treatment capabilities of the sepsis-related kidney injury are remarkably improved.

Provided herein are pharmaceutical compositions comprising carotenoids, including liposomes that encapsulate carotenoids including ionizable carotenoids such as trans-crocetin. The provided compositions have uses in treating diseases, disorders and conditions associated with, but not limited to, infection, endotoxemia, inflammation, sepsis, ischemia, hypoxia, shock, stroke, lung injury, wound healing, traumatic injury, reperfusion injury, cardiovascular disease, kidney disease, liver disease, inflammatory disease, metabolic disease, pulmonary disorders, blood related disorders and hyperproliferative diseases such as cancer. Methods of making, delivering, and using the pharmaceutical compositions are also provided.

The invention discloses a silicon shell protected magnetic quantum dot nanoprobe, a preparation method, a kit and application. The nanoprobe comprises a nanomaterial and a specific antibody, the nanometer material is of a core-shell structure, and the outer surface of a core is sequentially coated with an interlayer and a protective shell layer outwards. The interlayer comprises a multi-layer laminated structure formed by alternately arranging a plurality of layers of positive electricity interlayers and negative electricity interlayers; the positive electric interlayer is polyethyleneimine, the negative electric interlayer is quantum dots, the quantum dots are CdSe / ZnS or carbon quantum dots, amino groups on the surface of the shell layer and a dialkynyl polyethylene ethanol solution are subjected to general coupling of specific antibodies in a click chemistry mode by taking diyne molecules as connecting arms. The magnetic nanoprobe with the core-shell structure not only has strong magnetic responsiveness and a high fluorescence signal, but also can adapt to a complex environment, after the magnetic nanoprobe is integrated with an immunochromatography test strip, to-be-detected targets including pathogenic bacteria and inflammatory markers can be rapidly captured in a whole blood sample at the same time, and the magnetic nanoprobe has huge application potential in early diagnosis of sepsis.

The present disclosure relates to methods of treating sepsis or septic conditions in patients who have heightened LIGHT, IL-18 levels or biomarkers listed herein which can be treated with molecules that inhibit biomarker activity.

The invention provides a sepsis early-stage risk prediction system, and relates to the technical field of sepsis risk prediction, the sepsis early-stage risk prediction system comprises a data acquisition module, a data preprocessing module, a risk assessment module, a result display module and a data management module, and the data acquisition module is used for acquiring vital signs, laboratory data and medical record data through vital sign acquisition, laboratory data acquisition and medical record data acquisition; the data is collected from three aspects; the data preprocessing module can process the data and find features related to the early stage of sepsis from the collected data; the risk assessment module firstly scores, and determines whether machine prediction or expert prediction is performed according to the score level; and the result display module displays the evaluation result through visual display, and generates a report according to patient demands. The system has the advantages that multi-dimensional data such as vital signs of a patient, laboratory examination and electronic medical records are comprehensively collected through the data acquisition module, data islands are broken, and a rich information basis is provided for accurate prediction.

The invention discloses a macrophage-targeting inhalable nano material, a preparation method thereof and application of the inhalable nano material in treatment of sepsis myocarditis, and belongs to the technical field of medicines. The nano-material is a nano-liposome, the nano-liposome comprises a mannose modified nano-liposome microsphere, and the mannose modified nano-liposome microsphere comprises a liposome skeleton shell layer, a drug and a targeting layer; the liposome skeleton shell layer comprises soybean lecithin and cholesterol; the medicine comprises quercetin and TPPU (Thermoplastic Polyurethane); and the targeting layer is formed by connecting mannose modified DSPE-PEG2000 to the outer surface of the liposome skeleton shell layer. The nano material can accurately target macrophages at a cardiac inflammation part, has a multi-target-point synergistic effect, is more convenient and faster in administration, remarkably improves the safety and comprehensively improves the treatment effect.

The invention belongs to the field of biological medicines, and relates to a drug-loaded nano-vesicle as well as a preparation method and application thereof. The drug-loaded nano-vesicle comprises a vesicle core and a drug-loaded nano-vesicle, wherein the vesicle core comprises siRNA (small interfering Ribonucleic Acid) capable of specifically targeting and silencing an NR1D1 gene; the vesicle membrane is formed by fusing an erythrocyte membrane, a macrophage membrane, cardiolipin, cholesterol and lecithin. The drug-loaded nano-vesicle can specifically target macrophages in a sepsis immunosuppression stage, has an intracellular response release function, recovers BMAL1 and IGF2BP2-ATP6V1B2 / ATP6V0c axis functions by inhibiting NR1D1 expression, reconstructs a macrophage phagocytosis function and lysosome-dependent bacterium removal capability, and can be used for preparing a drug-loaded nano-vesicle with a specific targeting function. The survival rate of sepsis immunosuppression model animals is obviously improved; and the bacterial load is reduced. Compared with a traditional electroporation method, the preparation method disclosed by the invention has the advantage that the encapsulation efficiency of siRNA is remarkably improved.

The invention belongs to the field of traditional Chinese medicines, and particularly relates to a traditional Chinese medicine composition for treating sepsis-related acute lung injury and application thereof. The traditional Chinese medicine composition comprises the following active pharmaceutical ingredients in parts by mass: 5-15 parts of cassia twig, 5-15 parts of rheum officinale, 10-20 parts of peach kernel, 25-35 parts of gypsum and 10-20 parts of kudzu vine root. Animal experiments show that the traditional Chinese medicine composition can effectively improve lung tissue pathological manifestations of mice with sepsis-related acute lung injury by inhibiting polarization of M1 type macrophages, promoting polarization of M2 type macrophages, improving the infiltration level of neutrophils and inhibiting release of inflammatory factors. Therefore, the traditional Chinese medicine composition disclosed by the invention has a good treatment effect on acute lung injury related to sepsis.

The invention discloses a sepsis clotting disease subtype characteristic and typing system, which comprises a basic data acquisition module used for acquiring SIC patient characteristics; a potential category analysis module configured to identify potential groups of the SIC patients based on the SIC patient features; the K-means clustering module is configured to cluster the characteristics of the SIC patients and obtain a clustering result of the SIC patients; and the typing result output module is configured to output subtype features and typing results of the SIC patients based on the potential groups of the SIC patients and the clustering results of the SIC patients. The subtype classification of the SIC patient can be rapidly and accurately analyzed, and a direction is provided for subsequent treatment.

The invention discloses a sepsis typing division method and a typing prediction model construction and application method and device, and relates to the field of machine learning, and the method comprises the steps: obtaining central venous oxygen saturation and peripheral perfusion indexes of a plurality of patients in a preset time period; calculating and acquiring a dynamic blood flow oxygen flow index track of each patient in the preset time period according to the central venous oxygen saturation and the peripheral perfusion index of the patient in the preset time period; evaluating trajectory similarity by using a dynamic time warping algorithm, and grouping trajectories by using a hierarchical clustering algorithm to obtain a plurality of sepsis types; and training the machine learning model by using each sepsis type and the corresponding clinical features of the patient to obtain a sepsis type prediction model. According to the application, sepsis typing division is carried out based on the longitudinal data of the central venous oxygen saturation and the peripheral perfusion index, a prediction model is established for each typing based on clinical features, and finally division and accurate prediction of sepsis crowds are realized.

The invention relates to a training method of a respiratory tract infection disease progress and prognosis prediction model. The training method comprises the following steps: extracting mRNA from peripheral blood of a target patient, and carrying out transcriptome sequencing to obtain a sequencing result; based on the ferroptosis related gene set, comparing ferroptosis score differences of two groups of patients with community-acquired pneumonia and sepsis, and screening corresponding ferroptosis related genes with statistical significance from a sequencing result; screening out genes meeting preset conditions from the ferroptosis related genes based on LASSO regression; and establishing an RTI clinical outcome prediction model through logistic regression by taking whether the patient is sepsis or not as an outcome dichotomy variable and taking the screened gene expression quantity as a prediction variable. According to the invention, after the prediction model is subjected to machine learning screening such as LASSO and the like, the core feature with the highest prediction value is reserved, so that the risk of over-fitting of the model on training data is reduced.

The invention relates to the technical field of medical data mining, and particularly discloses an elderly sepsis index model, a prediction model construction method and a prediction system.The method comprises the steps that a development queue data set and an independent verification queue data set of elderly sepsis patients at the age larger than or equal to 60 years old are determined according to an intensive care database; performing sepsis death and prognosis importance sorting on candidate inflammation-immune composite indexes of the development queue data set according to a total correlation feature selection algorithm; superposing and combining preset basic indexes, each index in the importance inflammation marker indexes and a preset importance scoring standard; comparing the scoring results of the multiple groups of joint optimization index models, and evaluating the scoring results; and determining the joint optimization index model with the optimal evaluation result as the senile sepsis index model. According to the construction method of the senile sepsis index model provided by the invention, the index model suitable for senile sepsis can be obtained based on the existing index database.

The invention provides a mononuclear cell for treating sepsis cardiomyopathy, and also relates to application of the mononuclear cell in preparation of drugs for improving sepsis and sepsis cardiomyopathy. The mononuclear cell provided by the invention can have a better targeted enrichment characteristic, so that the effective rate of treatment is improved, and meanwhile, toxic and side effects caused by non-specific distribution of drugs are reduced. Besides, the mononuclear cells are derived from the body of a healthy body, so that the mononuclear cells are more stable in metabolism, higher in absorption efficiency and more excellent in enrichment effect when acting on the body, and the technical problems that in-vivo half-life period of drugs is short and catabolism is easy in the prior art are solved.

The invention discloses a group of pyemia specific biomarkers and application thereof, and belongs to the field of medical detection.The biomarkers are formed by combination of alpha 1-microglobulin / Bikunin precursor protein and one or more of antithrombin III protein, apolipoprotein A1 or apolipoprotein H, according to the invention, seven core proteins, namely APOA1, APOH, AMBP, SERPINC1, F2, FGG and FGB, are screened from TMT proteomics of serum of a clinical hemorrhagic patient, and four more important proteins, namely APOA1, APOH, AMBP, SERPINC1, F2, FGG and FGB, are obtained by further screening the seven proteins in a hemorrhagic cell model and the clinical hemorrhagic patient. The four proteins are verified again in serum of a hemorrhagic mouse animal experiment and an expanded-scale clinical hemorrhagic patient, and the potential of the four core proteins as serum biomarkers for early diagnosis of hemorrhagic disease is determined.

The invention discloses a sepsis blood perfusion dynamic monitoring method combining blood oxygen and blood flow parameters, and belongs to the technical field of medical monitoring. The method specifically comprises the following steps: S1, constructing a sepsis patient grading evaluation diagnosis and treatment model, and obtaining sepsis patient information, index data, sepsis severity at that time, a treatment scheme and post-treatment index data to train the model; s2, information and index data of current sepsis patients are collected, blood flow and blood oxygen are measured, the current sepsis patients are matched through the sepsis patient grading diagnosis and treatment model, the severity degree of sepsis of the current patients is judged, and the information, the index data and the severity degree of sepsis of the current patients are displayed. By acquiring basic information, physiological indexes, severity, treatment schemes and post-treatment data of sepsis patients, a database covering a whole diagnosis and treatment process is constructed, so that the model can learn association between different patient features and diagnosis and treatment results, and comprehensiveness of evaluation and prediction is improved.

The invention relates to the technical field of traditional Chinese medicine preparations, in particular to a traditional Chinese medicine compound preparation for preventing and treating sepsis based on intestinal treatment and gasification regulation and a preparation method and application of the traditional Chinese medicine compound preparation. The composition is prepared from the following medicinal materials in parts by weight: 3 to 10 parts of rheum officinale, 5 to 10 parts of fructus aurantii, 5 to 10 parts of radix aucklandiae, 10 to 15 parts of fructus gardeniae, 10 to 15 parts of dandelion, 10 to 15 parts of fructus forsythiae, 10 to 15 parts of herba artemisiae scopariae, 10 to 15 parts of rhizoma atractylodis, 10 to 15 parts of poria cocos, 10 to 15 parts of radix paeoniae rubra, 10 to 15 parts of radix salviae miltiorrhizae, 15 to 20 parts of astragalus membranaceus, 10 to 15 parts of rhizoma anemarrhenae, 10 to 15 parts of fructus cannabis, 10 to 15 parts of semen pruni and 3 to 6 parts of raw liquorice. The traditional Chinese medicine compound provided by the invention considers the treatment rules of relaxing bowels, purging heat, promoting qi circulation, removing stagnation, detoxifying, dispersing blood stasis, reinforcing qi, nourishing yin and the like, and also considers the effects of relaxing bowels, regulating qi and supporting healthy qi, various diseases of sepsis patients can be remarkably improved through the synergistic effect of the medicines in the formula, and the traditional Chinese medicine compound especially has an obvious curative effect on gastrointestinal dysfunction. A novel traditional Chinese medicine treatment thought is provided for clinical treatment of sepsis diseases.

The invention discloses a medicine composition for inducing fibroblasts to be reprogrammed into pericyte-like cells (PCLCs) through a chemical small molecule combination, and the medicine composition is used for treating sepsis. According to the invention, a chemical reprogramming strategy without genetic modification is adopted, an endogenous signal channel is activated through a time sequence, and fibroblasts from somatic cells are efficiently converted into PCLCs with high expression of genes such as EMILIN3, LAMC3, GDF10, AHR, CD109, AHR, NQO1, QPRT and the like. When applied to treatment of sepsis, the medicine composition can improve pathological symptoms and reduce death rate by synergistically exerting anti-inflammatory, anti-oxidation, immune regulation and tissue barrier protection effects. The invention provides a novel safe treatment strategy based on non-genetically modified cells for sepsis.

The present invention relates to the use of selective aquaporin inhibitors, e.g., of aquaporin-4 or aquaporin-2, e.g., certain phenylbenzamide compounds, for the prophylaxis, treatment and control of aquaporin-mediated conditions, e.g., diseases of water imbalance, for example edema (particularly edema of the brain and spinal cord, e.g., following trauma or ischemic stroke, as well as the edema associated with glioma, meningitis, acute mountain sickness, epileptic seizures, infections, metabolic disorders, hypoxia, water intoxication, hepatic failure, hepatic encephalopathy, diabetic ketoacidosis, abscess, eclampsia, Creutzfeldt-Jakob disease, and lupus cerebritis, as well as edema consequent to microgravity and / or radiation exposure, as well as edema consequent to invasive central nervous system procedures, e.g., neurosurgery, endovascular clot removal, spinal tap, aneurysm repair, or deep brain stimulation, as well as retinal edema), as well as hyponatremia and excess fluid retention, and diseases such as epilepsy, retinal ischemia and other diseases of the eye associated with abnormalities in intraocular pressure and / or tissue hydration, myocardial ischemia, myocardial ischemia / reperfusion injury, myocardial infarction, myocardial hypoxia, congestive heart failure, sepsis, and neuromyelitis optica, as well as migraines, as well as to novel assays for identifying aquaporin inhibitors.

The invention provides a risk prediction model for the death rate of senile sepsis patients in 28 days after the senile sepsis patients are transferred into ICU and a construction method of the risk prediction model, independent risk factors related to death occurrence in 28 days are determined through single-factor and multi-factor logistic regression analysis, a column chart is made, the prediction model of the patent is constructed, and the risk prediction model of the senile sepsis patients in 28 days can be used for predicting the death rate of the senile sepsis patients. A comparison result with a standard APACHE II score and a decline index (FI-lab) in recent years or an AUC of an ROC curve of other multi-index models shows that the prediction model provided by the invention is better in efficiency.

The invention provides a sepsis multi-task prediction method and system, and belongs to the technical field of disease prediction based on a mathematical model, and the method comprises the steps: obtaining a symptom data record of a to-be-detected patient; and processing the obtained symptom data records by using a pre-trained classification model to obtain a final task result. According to the method, a multivariable time sequence in medical health record data of a patient is utilized, time representation containing sepsis pathological characteristics is obtained through a time mode of modeling data based on a self-attention encoder, and the trend of the condition of the patient changing along with time is obtained; correlating different medical features according to features including patient condition change trends, so that each feature can perceive other features mutually, and mining global feature representation of the patient; and inputting the global feature representation into a task-aware hybrid expert system, and routing the unified global feature representation into different expert systems, thereby obtaining task-level representation and realizing multi-task prediction.

The invention discloses a sepsis multi-complication prediction method and system, a storage medium and equipment, and belongs to the technical field of intelligent medical treatment, and the method comprises the following steps: S1, collecting multi-dimensional time sequence physiological data of a sepsis patient; s2, constructing a medical perception feature vector for the time sequence physiological data; s3, constructing a sepsis multi-complication prediction model and introducing a physiological logic space-time composite mask matrix; s4, outputting a multi-complication prediction probability by adopting a hierarchical expert hybrid network H-MoE; s5, training the model by adopting a dynamic weighting loss function based on task uncertainty; s6, risk output and feature contribution degree explanation; according to the model, by introducing physiological logic masks and an H-MoE framework, precise and synchronous prediction of complex complications of sepsis is achieved, redundant features can be effectively filtered, complex association between the redundant features can be revealed, quantitative decision support is provided for clinicians, and therefore early intervention and personalized treatment are achieved.

The invention relates to a preparation method of exosome-like nano vesicles. The preparation method comprises the following steps: extracting beet juice; performing low-speed centrifugal treatment on the beet juice, and taking supernate; carrying out medium-speed centrifugation treatment on the supernatant obtained by low-speed centrifugation, and taking the supernatant; carrying out high-speed centrifugation treatment on the supernatant obtained by medium-speed centrifugation to obtain a precipitate containing exosome-like nano vesicles; and carrying out sucrose density gradient ultracentrifugation on the obtained precipitate containing the exosome-like nano-vesicles to obtain the purified exosome-like nano-vesicles. The BELNV prepared by the invention can significantly improve the survival rate of sepsis mice, increase blood perfusion of tissues and organs of the sepsis mice, reduce pathological changes, macrophage infiltration and fibrin deposition in lung and liver tissues of the sepsis mice, and reduce blood coagulation indexes and inflammation indexes. The invention provides a novel treatment target and strategy for a treatment means of sepsis-related blood coagulation dysfunction.

The invention relates to the technical field of medicine preparation, in particular to application of a microRNA244-5P inhibitor in preparation of a product for treating sepsis cardiomyopathy. According to the application of the microRNA 244-5P inhibitor in the preparation of the product for treating the sepsis cardiomyopathy, the sequence of the microRNA 244-5P inhibitor is shown as Seq. ID No. 1, and the microRNA 244-5P inhibitor can be applied to the preparation of the product for treating the sepsis cardiomyopathy. The provided microRNA 244-5P inhibitor lays a precise foundation for targeted treatment of sepsis cardiomyopathy. The inhibitor can specifically recognize and act on related targets, accurately intervene the pathological process of sepsis cardiomyopathy, has more stable structure and activity, can ensure that the inhibition effect can be continuously and efficiently played when a treatment product is prepared, provides a clear material basis and a technical basis for research, development, production and quality control of subsequent products, and has a wide application prospect. The pertinence and the effectiveness of treatment are greatly improved.

The invention relates to a biomarker applied to early diagnosis of sepsis. The biomarker is a fibrous protein degradation product FDP / D-dimer ratio. Compared with a single index (such as PCT, D-dimer), the biomarker has the advantages that the influence of individual difference and detection error can be reduced, and the stability of a result is improved; in combination with clinical information (such as infection evidence), the ratio can be used as an independent or joint index to assist an existing scoring system (such as SOFA) in improving diagnosis accuracy.

Provided herein are novel lipase inhibitors and methods for using the same to treat inflammation, multisystem organ failure, necrotic pancreatic acinar cell death, acute pancreatitis, sepsis (e.g., culture negative sepsis), burns, and acne. For example, provided herein are two novel lipase inhibitors useful in the methods described herein:or a pharmaceutically acceptable salt thereof.

The invention discloses application of ADAMTS4 as a biomarker of sepsis with cardiac dysfunction, AUCROC is equal to 0.930, 95% CI is 0.859-1.000 in diagnosis of sepsis with cardiac dysfunction as the biomarker, accuracy is high, and a new detection means and scheme are provided for diagnosis and prediction of sepsis with cardiac dysfunction.