58 results about "Inflammatory marker" patented technology

The invention discloses a fungus extract capable of effectively regulating uric acid metabolism and relieving inflammation as well as a preparation method and application of the fungus extract, and belongs to the technical field of deep processing of edible fungi. Schizophyllumcommuneh and poplar phellinus sporocarp are mixed and extracted, and the prepared fungus extract can effectively inhibit activity of xanthine oxidase in serum and liver of mice, reduce content of uric acid, creatinine, urea nitrogen and the like in serum and promote excretion of uric acid, creatinine, urea nitrogen and the like in urine; meanwhile, the content of inflammatory markers such as IL-6 and TNF-alpha in mouse serum can be effectively reduced, inflammatory infiltration of liver and kidney cells is relieved, and the problem that an existing edible mushroom extract is not ideal in treatment effect on hyperuricemia is solved.

The invention is applicable to the technical field of biological detection, provides a fluorescence immunochromatography detection method based on monatomic nano-enzyme enhancement, and particularly relates to two application forms: in the first form, a detection signal enhanced fluorescence immunochromatography detection card and a sample diluent containing a monatomic nano-enzyme are involved; in the second form, the invention relates to a fluorescence immunochromatography detection card with enhanced detection signals, and a sample pad of the detection card is obtained by soaking a sample pad treatment solution containing a monatomic nano-enzyme solution. The two application forms both relate to a monatomic nano-enzyme solution, and the solution is composed of monatomic nano-enzyme, bio-enzyme composite microspheres, a protective agent, a surfactant, a thickening agent and a preservative. The monatomic nano enzyme is composed of an atomic-scale dispersed metal active center and a carrier material. When the method is used for detecting myocardial and inflammatory markers, the limit of quantitation can reach the pg / mL level, the detection linear range can span three orders of magnitude, and the clinical examination use requirements can be met. The kit can be applied to rapid quantitative detection of myocardial and inflammatory markers, has the advantages of high sensitivity, rapidness, convenience and high efficiency, and provides an auxiliary diagnosis basis for early screening of myocardial infarction, heart failure and infection related diseases.

The invention discloses a post-stroke depression risk prediction system based on cerebral small vascular diseases and inflammatory markers, and relates to the technical field of computer-aided engineering, the post-stroke depression risk prediction system comprises: a data acquisition module acquires CSVD image data, serum inflammatory markers and clinical baseline information; the data preprocessing module processes image denoising registration, fills up marker missing values and encodes clinical information; the CSVD feature extraction module extracts image omics features and quantifies severity; the inflammation marker module calculates statistical characteristics and inflammation intensity; the multi-dimensional fusion module integrates features and eliminates redundancy; the risk prediction module is trained by using an improved attention CNN-LSTM model; the result output module visualizes risk and intervention suggestions; the model dynamic optimization module updates parameters by incremental learning. According to the method, multi-source key data are integrated, the prediction accuracy and generalization ability are improved, clinical interpretation and dynamic adaptability are achieved, early recognition of post-stroke depression is assisted, and patient prognosis is improved.

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.

Described herein are methods for treating antibody mediated rejection (ABMR), especially chronic active ABMR (cABMR), of transplanted organs using clazakizumab. Human kidney transplant recipients with biopsy-proven cABMR, transplant glomerulopathy and who are donor-specific antibody positive showed stabilization of renal function and lowered DSA levels following clazakizumab treatment. The estimated glomerular filtration rate of the patients at six, 12 or even 18 months were stabilized, inflammatory markers of cABMR were reduced or stabilized, and inflammatory blood markers were reduced, since clazakizumab treatment.

The invention discloses a method and system for predicting early infection of a child burn wound, and the method comprises the steps: S1, obtaining the information of the child burn wound, and monitoring the local temperature, pH value, specific inflammatory marker level and original data of pathogen nucleic acid of the burn wound; s2, generating a trend change comprehensive model by using a time sequence analysis algorithm; s3, key features are extracted through an adaptive feature selection technology trend change comprehensive model, and data dimensions are reduced; s4, adopting a transfer learning method to perform pre-training in the burn case as a risk assessment model, and utilizing the risk assessment model to generate an infection risk score; and S5, setting a risk threshold value, and when the infection risk score exceeds a preset threshold value, performing early warning, marking child wound infection, generating a detailed infection report, and performing targeted treatment. According to the method, the problem that a high-performance prediction model is difficult to directly construct due to relatively small child medical data volume and complexity is solved, and the ability of early infection recognition of children is improved.

A method of treating a human subject which is effected by intermittent inhalation of gaseous nitric oxide at a concentration of at least 160 ppm is disclosed. The method can be utilized for treating a human subject suffering from, or prone to suffer from, a disease or disorder that is manifested in the respiratory tract, or from a disease or disorder that can be treated via the respiratory tract. The disclosed method can be effected while monitoring one or more of on-site and off-site parameters such as vital signs, methemoglobin levels, pulmonary function parameters, blood chemistry and hematological parameters, blood coagulation parameters, inflammatory marker levels, liver and kidney function parameters and vascular endothelial activation parameters, such that no substantial deviation from a baseline in seen in one or more of the monitored parameters.

This invention relates to the field of medical information management technology, including an AI-based endometriosis management system. The system comprises a thickness dynamic monitoring module, an inflammation level assessment module, a lesion spread analysis module, a periodic lesion tracking module, and a disease progression analysis module. In this invention, AI is used to segment ultrasound image data, enabling dynamic monitoring of lesion areas. Lesion boundaries are extracted, and changes in local inflammatory marker concentrations are calculated, making the screening of abnormal inflammatory areas more accurate and enabling early identification of lesion development. The tracking of periodic lesions, combined with analysis of lesion contour changes and area increases / decreases, enhances the quantitative control of disease progression. The future development trend of lesions, combined with the calculation of periodic inflammatory pathways, makes the prediction of disease evolution more consistent with physiological changes. Multi-dimensional lesion analysis combined with AI intelligent calculation expands the diagnosis and treatment of endometriosis from static assessment to dynamic trend prediction, improving the adaptability of personalized treatment plans.

The application discloses a kind of elderly hip fracture surgery perioperative adverse event real-time monitoring system and method, it is related to perioperative monitoring technical field.The method includes: real-time acquisition perioperative monitoring data, carries out data pre-processing, and extracts benchmark feature;Identify the decline segment of cerebral oxygen saturation below benchmark feature, jointly assess the decline amplitude and persistence, obtain the weak trend characterization of brain oxygen;Analysis of the relative change characteristics of serum inflammatory markers, form the weak trend characterization of inflammation;Assess the deviation degree of vital signs relative to benchmark, obtain the vital signs fluctuation characterization, and further judge the delirium precursor risk, output risk prompt;Visual display various weak trend characterizations and delirium precursor risk, link label risk trigger information and contribution source.The present application solves the technical problems that the prior art is difficult to extract and identify early weak abnormal trend in perioperative multi-source physiological signals.

The invention discloses a detection method of inflammatory marker protein. According to the method, the micro-fluidic chip with a sample loading area, a buffer treatment area, a sample channel and a detection area is prepared on filter paper through wax printing; chitosan is preset in the sample loading area and is used for treating a sample, and bromothymol blue is fixed in the detection area and is used as a pH indicator. During detection, a sample is driven by a phosphate buffer solution with the pH value of 6.0 to flow to a detection area through capillary action, the C-reactive protein and the indicator are subjected to non-specific binding, so that the color of the detection area is changed from yellow to green, the length of a green developing signal is in direct proportion to the concentration of the CRP, and quantitative detection can be realized by measuring the length. The method does not need an antibody, is low in cost, is simple and convenient to operate, can complete detection within 15 minutes, has the detection limit of 1.56 ng / ml and the linear range of 5-25 ng / ml, and is suitable for rapid screening and field detection of basic medical institutions.

The present embodiments provide a plant-based lipid composition comprising high concentrations of long-chain omega-3 fatty acids, typically as fatty acid esters, comprising DPA, DTA, ETA, or ETrA, optionally with OA or ALA. These enriched lipid compositions have improved stability, and offer a sustainable source for these long-chain omega-3 fatty acids. In some embodiments, these enriched lipid compositions show enhanced modulation of inflammatory markers, such as inhibition of inflammatory cytokines, and offer nutritional or therapeutic value..

The invention discloses a system and a method for dynamically identifying vulnerable plaques of an intravascular ultrasonic image. According to the system, plaque evolution information of continuous IVUS image frames is extracted by constructing a feature extraction module based on a space-time convolutional neural network; combining limited OCT annotation data through a transfer learning model; the blood flow wall shear force and the inflammatory marker IL-6 are fused in a plaque rupture risk prediction matrix, and a new mathematical calculation model is provided to predict the plaque risk. The system supports real-time analysis in an interventional operation and automatically marks a high-risk plaque area, and the vulnerable plaque detection sensitivity can reach 94% or above. The hardware architecture comprises an image acquisition unit, a deep learning calculation module and a labeling interaction module; the software architecture comprises a plaque recognition engine, a shear force calculation module, a biological data fusion interface and the like. The system has the advantages of being easy and convenient to operate, high in real-time performance, high in accuracy and the like, and an efficient intraoperative plaque risk assessment tool is provided for interventional therapy.

The invention provides an EP300 detection preparation and application of EP300 in a product for treating rheumatoid arthritis, and relates to the technical field of biological medicines. The rheumatoid arthritis symptom is relieved by inhibiting EP300 gene expression, after EP300 is knocked down in human THP-1-derived macrophages, H3K18 lactylation expression is reduced, and after EP300 is knocked down in human THP-1-derived macrophages, EP300 and human synovial cells are co-cultured, so that the human THP-1-derived macrophages are subjected to H3K18 lactylation expression is reduced, the human THP-1-derived macrophages are subjected to H3K18 lactylation expression is reduced, and the human THP-1-derived macrophages are obtained. Through the crosstalk effect between human THP-1-derived macrophages and human synovial cells, the expression of inflammatory markers MMP3 and Fibronectin in the synovial cells can be remarkably inhibited, compared with a model group, the proliferation capacity of the synovial cells is weakened, a potential treatment target is provided for treating rheumatoid arthritis, and the application has the advantages that the application is easy to popularize and use, and the application has a wide application prospect. The pathogenesis of rheumatoid arthritis is perfected, and hope is brought to research and development of novel biomarkers for early diagnosis, targeted therapy and prognosis evaluation of rheumatoid arthritis.

The invention relates to the technical field of skin care, and particularly discloses a composition with a periorbital care effect and a preparation method thereof. According to the invention, Tieguanyin and lethariella cladonioides extracts are used as core active components, and nicotinamide is compounded as a synergistic component. The Tieguanyin extract and the lethariella cladonioides extract synergistically exert the effects of resisting oxidation, resisting inflammation and preventing melanin accumulation, and nicotinamide intervenes melanin transport and metabolism through multiple ways. All the components generate a remarkable synergistic effect, the active oxygen level and inflammatory marker expression can be synchronously reduced on the cellular level, synthesis and accumulation of melanin can be effectively reduced, and the anti-inflammatory and soothing characteristics are shown. Intracellular oxidative stress can be remarkably inhibited through synergism of the components, and the composition has wide application in skin care products, especially eye care products.

A sprayable polymeric scaffold composition for localized anti-inflammatory therapy is disclosed. The composition comprises lipid nanorods encapsulating inflammasome inhibitors, a thermogelling agent, and a thickening agent. The lipid nanorods, which can be formed using pyridoxine dipalmitate and DSPE-PEG (2000) carboxylic acid, inhibit NLRP3 and AIM2 inflammasomes, reducing inflammation. The thermogelling agent, such as poloxamer 407, enables the composition to transition from a fluid sol state at room temperature to a semi-solid gel state at body temperature, forming a localized gel film upon topical application. The thickening agent, such as mucin, enhances viscosity and provides additional anti-inflammatory effects. The composition delivers sustained release of encapsulated inhibitors, effectively reducing inflammatory markers and symptoms in conditions such as psoriasis. The sprayable scaffold offers a novel, localized treatment platform with improved skin penetration, ease of administration, and reduced systemic side effects.

This invention relates to methods and compositions useful in subjects suffering from or at risk of suffering from sepsis or other dysregulated inflammatory responses. It has been demonstrated that the CETP inhibitor obicetrapib not only preserved or increased HDL-C and Apo A1 levels, but also reduced an important pro-inflammatory marker, IL-1β, and significantly increased survival, relative to placebo, in a suitable sepsis mouse model. Thus, broadly stated, the present invention concerns the use of CETP inhibitors in the prevention, treatment, management or amelioration of sepsis, or other dysregulated inflammatory responses in a subject.

The invention provides a process for preparing a Biochanin A (BCA)-loaded hydroxypropyl methyl cellulose (HPMC) hydrogel aimed at promoting wound healing in diabetic patients. The hydrogel is prepared by dispersing HPMC in distilled water, followed by dissolving BCA into the mixture with continuous stirring, then storing under refrigeration. The therapeutic potential of Biochanin A (BCA) in promoting wound healing, is evaluated in rats induced with diabetes. The results showed that the BCA-loaded hydrogel accelerates diabetic wound repair by boosting antioxidant defenses via upregulating Nrf2 and related enzymes, suppressing inflammatory markers such as IL-1β, IL-6, TNF-α, COX-2, and TLR4, and stimulating angiogenesis through increased expression of TGF-β1, VEGF-A, and PDGFR. It promotes faster wound contraction, re-epithelialization, collagen deposition, granulation tissue formation, and neovascularization, potentially reducing the risk of complications like limb amputation. The invention offers a promising therapeutic approach for treating chronic diabetic wounds with improved healing outcomes.

A method to assess the disease status, determine the mean / average control of the disease and monitor the compliance to treatment over a period of time of a respiratory disease, comprising of predicting the degree of airway inflammation and disease activity by measuring the inflammatory markers, evaluating the mucosal integrity / damage by measuring the moisture levels of the exhaled air, evaluating the breathing function and obstruction by measuring the FEV1 value, and evaluating the symptom control by determining the COPD Score.

A pharmaceutical composition comprising bovine serum albumin (BSA) nanoparticles loaded with ibudilast for the treatment of osteoarthritis, the composition comprising: a) Ibudilast in an amount of 10 to 50 mg, b) bovine serum albumin in an amount of 50 to 150 mg / ml, c) Glutaraldehyde as crosslinking agent in an amount of 8%, d) sucrose in an amount of 5% as a cryoprotectant, e) water and ethanol as solvents, f) wherein the nanoparticles have a particle size of about 241 nm, a zeta potential of -38.1 ± 1.2 mV, a polydispersity index (pdi) of 0.09 ± 0.007, and an entrapment efficiency of about 69%, g) wherein the composition is effective in reducing inflammatory markers, increasing anti-inflammatory cytokines and improving antioxidant defense in osteoarthritic conditions.

Anti-inflammatory topical compositions are disclosed in which niacinamide and polylysine dendrimer synergistically reduce the release of inflammatory markers (e.g., IL-8) from skin cells. Also disclosed are anti-inflammatory topical compositions in which polylysine dendrimer and various plant extracts reduce the release of inflammatory markers (e.g., IL-8) from skin cells. The pro-oxidative activity of polylysine dendrimer may be reduced by including an antioxidant (e.g., tocopherol and / or tocopheryl acetate) to an anti-inflammatory topical composition. Anti-inflammatory topical compositions comprising polylysine dendrimer and niacinamide and / or plant extracts (e.g., aloe vera extract, edelweiss extract, scuatline, etc.) may be used for treating inflammatory skin conditions (e.g., acne) by reducing the release of inflammatory markers (e.g., IL-8) from skin cells.

The invention relates to an electrochemiluminescence sensor based on an intelligent controlled release-interface capture-self-enhancement mechanism and application of the electrochemiluminescence sensor in procalcitonin detection, and belongs to the technical field of electrochemiluminescence detection. Controllable release of signal molecules is achieved by packaging terpyridyl ruthenium through ZIF-8, meanwhile, a DNA layer rich in guanine is modified on an electrode interface, and the layer can serve as a nano trap to efficiently capture the signal molecules and can also serve as a co-reactant to achieve signal amplification. A DNA strand displacement reaction is utilized to regulate and control a target response release process, and detection is realized according to a quantitative relationship between the concentration of procalcitonin and an electrochemical luminescence signal. A labeling recovery method verifies that the recovery rate of the sensor in a human serum sample reaches 100.6-103.6%, good accuracy and precision are shown, and a reliable platform is provided for clinical detection of inflammatory markers.

The invention discloses an application of KL-6 alone or in combination with other immune inflammation markers in complex silicosis recognition and lung function injury evaluation. The invention firstly discloses application of KL-6 in preparation of a product for complex silicosis identification and lung function injury evaluation. The invention further discloses application of the KL-6 combined with other immune inflammation markers in preparation of products for complex silicosis recognition and lung function injury evaluation. According to the invention, KL-6 is taken as a core, LDH and ESR are combined to construct a diagnosis scheme, and complex silicosis and dust exposed persons or simple silicosis can be distinguished; meanwhile, KL-6 is in significant negative correlation with lung function parameters and can assist in evaluating the severity of diseases and the condition of lung function impairment. The method is rapid and accurate in diagnosis, easy and convenient to operate, controllable in cost, capable of achieving batch detection, suitable for health monitoring of high-risk occupational people and capable of providing efficient technical support for early recognition of complex silicosis, lung function injury evaluation and clinical decision making.

The invention relates to the technical field of re-admission risk dynamic prediction methods, in particular to an AECOPD disease and symptom combined re-admission risk dynamic prediction method based on multi-algorithm fusion, which comprises the following data: (1) multi-source heterogeneous data: acquiring western medicine clinical data of a patient through a hospital information system (HIS); comprise lung function indexes, arterial blood gas analysis, inflammatory markers, the number of complications, the previous hospitalization frequency and the like; (2) dynamic monitoring of data: acquiring daily oxyhemoglobin saturation, heart rate variability and six-minute walking distance after hospital discharge through a wearable device; according to the AECOPD disease and symptom combined re-admission risk dynamic prediction method based on multi-algorithm fusion, on the basis of syndrome data of four diagnosis instruments of traditional Chinese medicine, AECOPD disease and symptom characteristics and a re-admission risk dynamic prediction method are fused, a disease and symptom fusion characteristic engineering system is constructed, deep coupling of western medicine and traditional Chinese medicine characteristics is achieved, and a traditional prediction model data barrier is broken through; by introducing spatial-temporal feature dynamic construction, complete-cycle description of a disease process is realized, and a multi-algorithm fusion architecture is innovated.

This invention discloses a traditional Chinese medicine composition for treating ulcerative colitis, its preparation method, combined drugs, and applications. The traditional Chinese medicine composition for treating ulcerative colitis of this invention is made from the following raw materials in parts by weight: Astragalus membranaceus 13-26 parts, Lonicera japonica 10-20 parts, Sargentodoxa cuneata 10-20 parts, Prunus mume 8-16 parts, Agrimonia pilosa 8-16 parts, Allium macrostemon 6-12 parts, Platycodon grandiflorus 6-12 parts, Coptis chinensis 3-6 parts, and Panax notoginseng powder 1-3 parts. An animal model of ulcerative colitis was constructed using DSS induction, and the results showed that the traditional Chinese medicine composition of this invention has a certain therapeutic effect on ulcerative colitis. Clinical studies showed that the traditional Chinese medicine composition of this invention, used in combination with mesalazine enteric-coated tablets, can reduce the modified Mayo score and serum inflammatory markers in patients with active ulcerative colitis, improve colonic mucosal inflammation and gastrointestinal symptoms, and effectively treat active ulcerative colitis of the damp-heat type.

The invention discloses a silicon shell protected Escherichia coli multifunctional probe, a preparation method and application of the probe in inflammatory marker detection, the surface of Escherichia coli is sequentially coated with a layer of gold nanoparticles (AuNPs), a layer of silicon dioxide (SiO2) and two layers of quantum dots (QDs), and rapid monitoring of sepsis biomarkers is achieved. The SiO2 layer introduced into the EASi-QDs structure has dual functions of remarkably enhancing the structural stability of bacterial cells and effectively inhibiting the fluorescence quenching effect caused by Au NPs, so that the high sensitivity and accuracy of lateral flow immunochromatography (LFIA) detection are ensured. The EASi-QDs-LFIA has the functions of colorimetric qualitative detection and fluorescent quantitative analysis, and can be used for synchronously detecting two key sepsis markers, namely procalcitonin (PCT) and interleukin-6 (IL-6). The detection limits of the method on PCT and IL-6 respectively reach 29.5 pg / mL and 4.7 pg / mL, which are respectively improved by at least 15 times and 339 times compared with the traditional enzyme-linked immunosorbent assay (ELISA) and gold nano colorimetric method.

The invention discloses a system and a method for determining early cancer risk influence factors. The method comprises the following steps: taking blood routine, blood biochemical and tumor marker data of a cancer group; determining a peripheral blood-derived inflammatory marker for the group of cancers; comparing the tumor marker data and the peripheral blood-derived inflammatory marker with corresponding data of a corresponding normal group, and determining a key abnormal factor with statistical significance; constructing a Lasso regression model based on all the key abnormal factors, and screening out a first-level influence factor from all the key abnormal factors according to the selected target parameters; a single-factor logistic regression analysis and parameter estimation method is utilized to screen out second-level influence factors from all the first-level influence factors; and a multi-factor logistic regression analysis and parameter estimation method is utilized to determine a significant impact factor from all the secondary impact factors. According to the method, the obvious influence factors on the early-stage cancer can be more effectively determined, and the accuracy and the reliability of cancer risk early warning are improved.

The invention discloses an application of plant lactobacillus GOLDGUT-HNU082 in relieving side effects of tumor drugs, and the preservation number of the plant lactobacillus GOLDGUT-HNU082 is CGMCC (China General Microbiological Culture Collection Center) NO.33075. The invention further discloses a preparation method of the plant lactobacillus GOLDGUT-HNU082. The bacterium can obviously relieve liver and intestinal injury caused by gefitinib, and the liver and intestinal injury shows that liver transaminase is reduced, inflammatory markers are reduced, and liver and intestinal tissue structures are more complete. In addition, the bacterium also remarkably improves the generation of short-chain fatty acid, and the regulation effect of the bacterium on the intestinal microecology is further proved. The research aims at exploring the relieving mechanism of probiotic mediated intestinal flora on the side effect of the medicine, promoting the probiotics to become an accompanying product of the gefitinib medicine, remarkably improving the side effect of the medicine and reducing the psychological burden of a patient to take the medicine.

A pharmaceutical composition comprising HLA-A2-expressing mesenchymal stem cells as an effective ingredient and its use in prevention or treatment of inflammatory disease are disclosed. The mesenchymal stem cells expressing HLA-A2 on the surface thereof inhibit the secretion of the inflammatory cytokine TNF-a and increase the expression of the anti-inflammatory markers CD163 and Arg-1, so that the pharmaceutical composition comprising the mesenchymal stem cells as an effective ingredient can be advantageously used for suppressing inflammation or treating inflammatory diseases.

The invention relates to the field of biological detection, in particular to a marker and application thereof in construction of a preeclampsia prediction model. The invention provides a marker, which comprises a red blood cell index and an inflammation marker; the red blood cell indexes comprise red blood cell count, hemoglobin, hematocrit, average red blood cell volume, average red blood cell hemoglobin and red blood cell distribution width variable coefficient; the inflammatory markers comprise leukocytes, neutrophils, lymphocytes, monocytes, platelets, eosinophils, platelet hematocrit, a systemic inflammatory response index and a systemic immune inflammatory index. The invention develops an efficient and easily available preeclampsia prediction tool, realizes early recognition and management of preeclampsia, and finally reduces maternal and infant complications.

The invention discloses a chronic disease risk early warning method, system and equipment based on inflammatory markers and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring case information and sign information of a target patient, wherein the case information comprises a historical inflammation marker detection record, a chronic disease type and a medication scheme; according to historical inflammatory marker detection records, calculating reference values of multiple inflammatory markers; based on the chronic disease type, screening out an inflammatory marker combination, and correcting the reference value of each inflammatory marker in the inflammatory marker combination based on the medication scheme to obtain an initial early warning threshold group; compensating the initial early warning threshold value group in combination with the physical sign information to obtain a target early warning threshold value group; and collecting a current inflammatory marker detection value, and when any index in the inflammatory marker detection value is greater than or equal to a corresponding index threshold in the target early warning threshold group, generating chronic disease risk early warning information. By implementing the technical scheme provided by the invention, the accuracy of chronic disease risk early warning can be improved.