32 results about "Perioperative" patented technology

The invention discloses a postoperative sub-delirium syndrome risk prediction system for a cardiac surgery patient, and relates to the technical field of medical treatment, and the system comprises a clinical data collection module which is used for collecting multi-dimensional clinical data of the cardiac surgery patient in a perioperative period under extracorporeal circulation, the data comprises patient baseline information, preoperative neurocognitive function evaluation indexes, intraoperative physiological parameters and postoperative early-stage vital signs; and the risk identification module is used for utilizing a single-factor statistical analysis mechanism. According to the postoperative sub-delirium syndrome risk prediction system for the cardiac surgery patient, accurate prediction of the sub-delirium syndrome risk is achieved by collecting multi-dimensional clinical data of the patient in the perioperative period, such as baseline information, preoperative neurocognitive function, intraoperative physiological parameters and postoperative early-stage vital signs; the independent risk factors are scientifically screened and quantified by using single factor analysis and a multivariate Logistic regression model, and the problem of incomplete data dimensions in traditional evaluation is effectively solved.

The invention relates to the technical field of wisdom medical treatment, in particular to a wisdom medical data self-supervision deep processing analysis system, which comprises a multi-department data sensing layer for acquiring multi-department data and postoperative follow-up visit data of a patient; the operation period feature processing center extracts data features of all departments, correlates data before and after an operation through an attention mechanism, and generates a patient perioperative period unified feature map; the full-cycle dynamic analysis unit analyzes the state of the patient in stages based on the patient perioperative period unified characteristic spectrum, and outputs a risk index in combination with a self-supervised training prediction model; the adaptive clinical decision module generates customized suggestions for different departments according to the analysis result and the risk index; the cross-department data collaboration unit is used for constructing a visual collaboration platform, so that doctors of all departments share and interact with a whole-cycle analysis result of an operation; and the dynamic feedback optimization unit collects clinical diagnosis and treatment results and performs reverse fine tuning on parameters of the self-supervised model. Therefore, the problems of strategy solidification, insufficient energy utilization efficiency and the like in the prior art are solved.

The invention discloses an intelligent assessment and auxiliary decision-making system for a perioperative period of a high-risk surgical patient, and belongs to the technical field of intelligent medical treatment. Comprising a set definition module used for defining a perioperative period state set; the logic set binding module is used for presetting a state binding logic set; the data migration module is used for inputting the multi-source heterogeneous perioperative period data into the state migration engine; the logic set activation module is used for dynamically adjusting the monitoring frequency, the early warning threshold and the decision support focus; the suggestion generation module is used for generating instant early warning and intervention suggestions; and the data recording module is used for feeding back and recording. According to the method, the dynamic state transition mechanism is constructed, and the corresponding monitoring and decision logic is bound for each state, so that the problems of early warning lag, untimely intervention and easy interruption of an intelligent management process caused by disconnection of system response logic and a clinical actual stage in the prior art are solved.

The invention belongs to the technical field of biological medicine, and discloses a portal cholangiocarcinoma postoperative risk prediction model based on a gamma-glutamyltransferase (GGT) dynamic change track and a construction method thereof. The method comprises the following steps: (1) collecting clinical characteristic data and survival characteristic data (including survival time and survival state) of a patient suffering from porta hepatis cholangiocarcinoma subjected to radical resection; 2) on the basis of GGT detection results at different time points in a perioperative period, dividing patients into different GGT dynamic change track types by using a latent category hybrid model; and 3) taking the clinical characteristic data and the GGT dynamic change track type as independent variables, taking survival data as response variables, screening prediction factors through LASSO regression, and constructing a multi-factor Cox regression model, namely a postoperative risk prediction model. According to the method, the dynamic evolution rule of the GGT is introduced, so that the limitation of single-time static detection is made up, the quantitative evaluation of the survival risk is realized, and a scientific basis is provided for individualized treatment and follow-up visit management.

The application discloses a brain hemorrhage perioperative medication scheme intelligent recommendation method and system, acquires physiological parameters and operation time sequence characteristics of a patient, constructs a patient risk image, carries out risk matching with a drug knowledge base to generate a candidate drug set, extracts drug attribute characteristics to determine a drug function grouping, carries out adaptability scoring based on the patient risk image to generate a grouping adaptability matrix, carries out drug interaction analysis to identify synergistic pairs and antagonistic conflict pairs, carries out combination optimization on the synergistic pairs to generate a synergistic scheme, carries out conflict exclusion screening on the antagonistic conflict pairs to generate safety constraints, constructs a medication scheme topology, carries out dose sensitivity anomaly detection and correction to generate a correction factor to generate a time-sharing drug administration scheme, carries out real-time monitoring to carry out perfusion evaluation to determine a safety level and trigger dose adjustment, forms an optimized medication scheme, and realizes intelligent recommendation of perioperative medication.

The utility model discloses a medical anti-slip, convenient flushing, pressure measurable single 'J' tube, which comprises a single J tube annular part and a single J tube main body, the right end of the single J tube main body is provided with the single J tube annular part, the left end of the single J tube main body is provided with a single J tube side branch, the lower side of the single J tube side branch is provided with a drainage bag, and the drainage bag is provided with a drainage hole. The single J tube collateral branch is connected with the drainage bag through a collateral branch flushing sampling end, and is used for a patient subjected to ureteral skin stoma pelvis ureteral drainage after radical bladder resection, the postoperative ureteral stent can be better prevented from slipping, the postoperative ureteral stent can be conveniently flushed, necrotic tissues and foreign matters can be flushed out in time, flushing and pressure measurement are facilitated due to sufficient drainage, and the drainage effect is good. Risks of hydronephrosis and exuresis caused by blockage of the ureteral stent after the operation of a patient are reduced, sampling after the operation is convenient, the condition of intrarenal pressure of the patient is known in time, and the problems that the ureteral stent slips easily and is difficult to wash in the perioperative period are solved.

Abstract The invention relates to a perioperative cobotic system designed to monitor, assess, and manage bioburden in real-time within operating room environments during surgical procedures and turnover phases. The system includes a mobile base equipped with a drive mechanism for maneuverability, a camera to capture image data, an actuator for camera movement, and a biosensor for direct bioburden assessment. Abstract assessment. 20 26 20 16 37 04 M ar 2 02 6 A b s t r a c t 2 0 2 6 2 0 1 6 3 7 0 4 M a r 2 0 2 6 a s s e s s m e n t .

The invention discloses a plasma metabolism biomarker combination for predicting and intervening propofol-induced respiratory depression, a detection method and application, and relates to the technical field of biological science. According to the method, non-target metabonomics detection is conducted on preoperative plasma of 298 subjects through UPLC-MS, 14-metabolite panels are obtained through machine learning supervised feature screening, a diagnosis model is established through verification of discovery and verification queues, and the prediction AUC of severe respiratory depression reaches 0.86-0.91 (discovery queue) and 0.86-0.91 (verification queue). Mouse in-vivo function verification proves that the key metabolite alpha-linolenic acid obviously improves the respiratory rate, the tidal volume and the minute ventilation volume under two administration paradigms of pretreatment and treatment of a mouse propofol-RD model, shortens the recovery time of righting reflex, has a good safety foundation, and has a good application prospect. Prompt can be converted into a foresight supplement or rapid treatment medication thought in a perioperative period, and a'prediction and intervention 'integrated clinical value is formed.

Randomization methods for healthcare scheduling optimization using perioperative stages. Poor scheduling of surgical appointments and procedures in operating rooms can lead to unnecessary downtime, and therefore loss of efficiency. The randomization methods include various probability models, Monte Carlo simulations, and stochastic optimization is used to optimize procedure scheduling in operating rooms. The optimized schedule may be based on estimated procedure duration, estimated turn-around-time, estimated cancellation frequency, forecasted emergency operating room usage, estimated surgeon utilization, and hospital site configuration. A probabilistic machine learning model may be trained based on historic data and ongoing performance data to automate the optimization process and increase accuracy based on up-to-date information and statistics.

The invention provides an eCRSwNP nasal endoscopic postoperative treatment method for regulating acidophilic granulocyte activity based on acupuncture, and relates to the technical field of traditional Chinese medicine for preventing and treating nasosinusitis diseases. According to the eCRSwNP nasal endoscopic post-operation treatment method for adjusting the acidophilic granulocyte activity based on acupuncture, accurate adjustment of the acidophilic granulocyte activity is achieved through a synergistic scheme of a nasal endoscopic operation, perioperative drug treatment and standardized acupuncture treatment, the postoperative recurrence rate is reduced, and the nasal symptom and life quality of a patient are improved. Acupuncture point selection, operation specifications, treatment frequency and treatment course of acupuncture are defined, a repeatable and generalizable standardized treatment scheme is formed in combination with strict patient screening standards, a quality control system and ethical guarantee, the technical problems that existing eCRSwNP postoperative treatment is lack of targeted immunoregulation means and the recurrence rate is high are solved, and the therapeutic effect of the eCRSwNP postoperative treatment is improved. And a new clinical path is provided for traditional Chinese medicine intervention on refractory nasosinusitis diseases.

The invention belongs to the field of medicines, and discloses application of macastine B in preparation of anti-inflammatory, repair-promoting and relapse and metastasis-resisting medicines after liver cancer operation. The invention discloses an application of macastine B in preparation of a medicine for recovering a liver cancer patient after partial liver resection. The macaxantin B can promote liver function recovery, reduce the level of inflammatory factors of liver tissues and serum species, and reduce the tumor recurrence rate and the tumor visceral metastasis rate after tumor excision after an orthotopic liver cancer surgical operation, and compared with simultaneous administration of a liver protection drug and an anti-tumor drug, the macaxantin B has the advantages that the liver metabolism burden is reduced, and the curative effect is improved. And a novel drug treatment choice is provided for disease management of a liver cancer patient in a perioperative period. The invention discloses a medicine for promoting postoperative recovery of an orthotopic liver cancer surgical operation. The medicine comprises an effective therapeutic dose of macastine B and pharmaceutically acceptable auxiliary materials.

The invention discloses a body temperature adjusting system based on digital twinning and an adjusting method thereof, and relates to the technical field of body temperature management. According to the system, multi-dimensional physiological data of a patient, operation related data, operating room environment data and heat preservation equipment operation state data are obtained in real time through a data acquisition module, a patient body temperature digital twin model is constructed, and the model is dynamically updated and calibrated in the operation process; the body temperature change trend of the patient is predicted based on the digital twinborn model, an individualized body temperature adjusting strategy is generated before the body temperature deviates from a preset safety threshold value, a plurality of devices such as body surface heating, infusion heating, flushing fluid heating and environment adjusting are coordinated through the cooperative control module for cooperative execution, and accurate regulation and control of the body temperature are achieved. Real-time mapping, predictive adjustment and closed-loop optimization of the body temperature of the patient can be achieved, the risk of low body temperature and excessive heat preservation in the perioperative period is effectively reduced, the safety and the intelligent level of body temperature management are improved, and good clinical application value is achieved.

Systems, devices and methods are disclosed for the treatment of injured peripheral nerves or other tissue using electrical stimulation. The systems can be used either in intraoperative or peri-operative settings and incorporate the use of either a plurality of monopolar electrodes with a patch used as return or a plurality of bipolar electrodes such as a cuff. The systems can provide hands-free delivery of electrical stimulation therapy over a predetermined set of time.

The application discloses an anesthesia hypotension prediction method and system based on FMD data mining of a grey system, and belongs to the field of electric digital data processing. The application carries out preprocessing, interval grey number conversion and dimension standardization processing on brachial artery blood flow mediated vasodilation function data and clinical baseline data, generates a standardized interval grey number feature set, completes feature screening and coupling relationship mining through grey nonlinear correlation analysis, completes risk simulation calculation through a non-equidistant metabolism GM(1, N) power model, and divides and outputs a hypotension risk level after anesthesia induction relying on grey clustering evaluation. The system is electrically connected by multiple functional modules in sequence, and can realize missing data completion, model precision verification and feature contribution output. The application is suitable for a poor information small sample scene, reduces the interference of data uncertainty and dimension difference, improves the reliability and interpretability of risk prediction, and provides evaluation support for perioperative hemodynamic management.

The embodiment of the invention provides a hypothermia risk prediction method, system and device, a storage medium and a program product. According to the scheme provided by the embodiment of the invention, the risk prediction model is utilized to determine the hypothermia occurrence probability of the patient in the perioperative period on the basis of the basic information, and the hypothermia occurrence probability of the patient is displayed and / or broadcasted through the main control equipment, so that a reference can be provided for medical staff in advance, the medical staff can make certain preventive preparations in advance, and the medical staff experience is improved. The occurrence probability of low body temperature is reduced, and the body temperature of the patient in the perioperative period can be managed more accurately. In the embodiment of the invention, the main control equipment can also determine at least one target heating device needing to work and the working parameters corresponding to the at least one target heating device according to the low body temperature occurrence probability, so that the main control equipment can automatically control the at least one target heating device to work; and the body temperature of the patient is kept in a relatively safe range.

Herein is provided a method of reversing ticagrelor-enhanced bleeding in a patient comprising administering to said patient during surgery, in a perioperative setting, or during an invasive procedure an antibody or antigen-binding fragment thereof that binds to ticagrelor. Also provided is a method of reversing ticagrelor-enhanced bleeding in a patient comprising administering an antibody or antigen-binding fragment thereof that binds to ticagrelor, wherein the patient is elderly, has underlying cardiac or pulmonary or metabolic disease, optionally wherein the patient has a minimum percent inhibition of P2Y 12 reaction units (PRU) over 4 hours after starting administration of the antibody or antigen-binding fragment thereof that is less than the percent inhibition of PRU before administration.

The invention discloses an intelligent pre-warning system for a perioperative period of a high-risk surgical patient, and belongs to the technical field of medical informatization. Comprising an information generation module used for generating initial early warning information; the information pushing module is used for providing priority adjustment feedback options during terminal display; the feedback receiving module is used for receiving priority adjustment feedback; the data capturing module is used for capturing a data context related to the early warning information; the score calculation module is used for generating dynamic priority correction rules and calculating a confidence score for each rule; the priority adjusting module is used for adjusting the priority of the new early warning information; and the iterative optimization module is used for carrying out iterative optimization on the dynamic priority correction rule. According to the invention, by constructing a dynamic priority correction mechanism based on clinical feedback, the technical effect of accurately matching the early warning priority with the clinical actual demand is achieved, and the problem of false alarm and missing alarm caused by rigid priority setting of a traditional early warning system is solved.

The invention discloses a psychological pre-rehabilitation and nursing intervention system for a perioperative period. The system comprises the following modules: a terminal module; the data acquisition and fusion module is used for collecting a subjective scale, behavior data, physiological data and medical data; the evaluation and layering engine is used for carrying out evaluation and layering by adopting a multi-modal fusion interpretable machine learning algorithm based on the data of the data acquisition and fusion module, and outputting interpretable feature importance and preoperative time axis sensitivity; the intervention prescription generator is used for forming and outputting an intervention packet based on the evaluation and layering engine output result; the intervention execution and adaptation module can adapt to schedules and has a reminding function; the risk detection and early warning module can prompt risks based on rules or models; and the result evaluation and report module can automatically generate a report and examine the indexes. The method is used for solving the problems of lack of closed loop, weak individualization and difficulty in quantification, and the preoperative psychological preparation and postoperative recovery quality are improved.

This invention discloses a method, device, and electronic device for perioperative medication management. The method includes: acquiring user time window data, surgery type data, surgical medication data, user basic data, and user long-term medication data; performing multidimensional cross-analysis on the surgery type data, surgical medication data, user basic data, and user long-term medication data to identify potential drug interactions and perioperative risk points; performing dynamic time-series analysis on potential drug interactions and perioperative risk points based on time window data to obtain medication adjustment suggestions for the user in any target time window; and generating targeted medication adjustment suggestions for any target time window. This achieves personalized and dynamic management of perioperative medication, effectively reducing the risk of drug interactions and improving the safety and rationality of perioperative medication.

The utility model relates to a kind of perioperative arm belt type insulin pump fixing sleeve, including containing bag and fixed ring, the fixed ring includes half ring one, the left end fixed mounting of half ring one has rotating rod, the left side rotating installation of rotating rod has half ring two, the bottom of half ring one is provided with limiting piece;The limiting piece includes box, the bottom fixed mounting of half ring one has box, spring is fixedly installed on the inner bottom wall of box, the top fixed mounting of spring has support frame.The perioperative arm belt type insulin pump fixing sleeve, by the rotating connection of half ring one and half ring two and the design of limiting piece, fixed ring can be personalized adjustment according to the arm thickness of patient, ensure the best fixing effect and comfort, the design of gear and clamping groove in limiting piece, so that fixed ring can be automatically locked after being adjusted to suitable range, realize stable fixation, avoid the problem of easy to fall off in traditional fixed mode.

The application discloses an AI model-based perioperative medical detection image accurate analysis and management system and method, and relates to the technical field of medical image processing. The AI model-based perioperative medical detection image accurate analysis and management system and method comprises the following steps: S1, preprocessing chest radiograph structure feature data and historical statistical data of a surgical patient in a perioperative period; S2, discriminating and segmenting a structure overlapping area by gradient field response and geometric density correction for the overlapping structure area; S3, constructing a time sequence registration criterion by adopting a structure-guided rigid and affine joint registration algorithm; S4, fusing time sequence labels by fusing response and space fluctuation suppression; and S5, constructing, training and reasoning a structure function evaluation model by adopting multi-modal feature enhancement. The technical problem that data labels are confused due to structure overlapping and time sequence changes in the prior art AI analysis of chest radiographs in a perioperative period, and the stability and accuracy of AI model training and reasoning are affected is solved.

Herein is provided a method of reversing ticagrelor-enhanced bleeding in a patient comprising administering to said patient during surgery, in a perioperative setting, or during an invasive procedure an antibody or antigen-binding fragment thereof that binds to ticagrelor. Also provided is a method of reversing ticagrelor-enhanced bleeding in a patient comprising administering an antibody or antigen-binding fragment thereof that binds to ticagrelor, wherein the patient is elderly, has underlying cardiac or pulmonary or metabolic disease, optionally wherein the patient has a minimum percent inhibition of P2Y12 reaction units (PRU) over 4 hours after starting administration of the antibody or antigen-binding fragment thereof that is less than the percent inhibition of PRU before administration.

The invention relates to the technical field of medical treatment, and discloses a surgical site infection early warning method and device, a terminal and a storage medium, and the method comprises the steps: obtaining perioperative period electronic medical record data of a target patient, the electronic medical record data comprising structured clinical indexes and unstructured text records; performing standardization processing on the structured clinical indexes to generate a first type of feature variables, performing natural language processing on the unstructured text records to obtain at least one medical entity related to surgical site infection, and generating a second type of feature variables based on context semantic information of each medical entity; fusing the first type of feature variables and the second type of feature variables to form a candidate feature matrix; inputting the candidate feature matrix into a pre-trained risk prediction model to output a risk result of surgical site infection of the target patient; wherein the risk prediction model comprises a plurality of base learners, a meta learner and a dynamic selection layer.

The application relates to the technical field of medical treatment and discloses a surgical site infection early warning method and device, a terminal and a storage medium. The method comprises the following steps: obtaining perioperative electronic medical record data of a target patient, wherein the electronic medical record data comprises structured clinical indexes and unstructured text records; performing standardization processing on the structured clinical indexes to generate first-type characteristic variables, and performing natural language processing on the unstructured text records to obtain at least one medical entity related to surgical site infection and generate second-type characteristic variables based on context semantic information of each medical entity; fusing the first-type characteristic variables and the second-type characteristic variables to form a candidate characteristic matrix; inputting the candidate characteristic matrix into a pre-trained risk prediction model to output a risk result of surgical site infection of the target patient; and wherein the risk prediction model comprises a plurality of base learners, a meta-learner and a dynamic selection layer.

The invention discloses an anesthesia depth monitoring method based on electroencephalogram micro-state and detrending fluctuation analysis, which comprises the following steps: acquiring multi-channel electroencephalogram data of different anesthesia processes in a database, and preprocessing the electroencephalogram data; extracting a micro-state sequence x (t) from the preprocessed electroencephalogram data; mapping the micro-state sequence x (t) into a numerical sequence and dividing the numerical sequence into a plurality of sub-data segments X (n); fitting a detrending fluctuation function F (n) on multiple scales for each sub-data segment X (n); and performing linear fitting on the F (n) obtained by calculation under each scale, and selecting an average value of slopes of the F (n) under each numerical distribution condition as an anesthesia depth evaluation index MS-HE. According to the method, the anesthesia depth in the perioperative period can be measured more comprehensively, and the evaluation accuracy is improved.

This application discloses an insulin pump dose adjustment method, system, device, and storage medium. The insulin pump dose adjustment method includes acquiring the target user's electronic health record, real-time blood glucose data, and perioperative stress index data, wherein the perioperative stress index data includes the target user's surgical type and anesthesia method; inputting the electronic health record, real-time blood glucose data, and perioperative stress index data into a trained insulin pump dose prediction model to obtain the insulin dose prediction result output by the trained insulin dose prediction model; and converting the insulin dose prediction result according to a preset standardized format to obtain a standardized insulin dose prediction result, which meets the blood glucose management needs of the user during the perioperative period.

The application discloses a perioperative hypothermia management method and system, wherein the management method comprises the following steps: acquiring the surface temperature time series data of a target patient in a perioperative period in real time; converting the surface temperature time series data into core temperature change characteristics based on a pre-constructed body temperature conversion model, wherein the body temperature conversion model is constructed based on the correlation between the surface temperature time series data and the core temperature change characteristics; dynamically evaluating the hypothermia risk of the target patient based on the core temperature change characteristics to obtain a dynamic risk evaluation result; and automatically controlling a heating device based on the dynamic risk evaluation result. The surface temperature time series data is converted into core temperature change characteristics through the body temperature conversion model. The risk caused by invasive measurement is avoided, the accuracy of non-invasive body temperature monitoring is improved, and the patient's body temperature is dynamically adjusted by automatically controlling the heating device to automatically heat or stop heating in real time according to the dynamic risk evaluation result, so that automatic body temperature regulation is realized.

This invention relates to the fields of biotechnology and pharmacogenomics detection, and discloses a kit and application for gene detection of drugs used in general anesthesia. The kit contains a primer set for detecting genetic polymorphic loci related to commonly used perioperative anesthetic, analgesic, and muscle relaxant drugs. The primer set includes multiplex PCR amplification primers and single-base extension primers. The kit also includes multiplex PCR amplification reaction solution, SAP reaction solution, SAP enzyme, extension buffer, single-base extension termination mixture, extension reaction enzyme, desalting purification resin, standards, calibrators, deionized water, and instructions for use. This invention uses matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF) to genotype SNP loci, obtaining genotype results for 103 genetic polymorphic loci in a single test. This allows for the prediction of individual differences in drug metabolism, drug efficacy, and adverse reaction risk, providing a basis for personalized medication in general anesthesia.

The present invention relates to use of an adenylyl cyclase inhibitor represented by formula (1) or a pharmaceutically acceptable salt thereof in the preparation of a drug for treating perioperative pain. The perioperative period comprises a preoperative period, an intraoperative period, and a postoperative period. The drug comprises an active ingredient for gastrointestinal or non-gastrointestinal administration, and a suitable pharmaceutical organic or inorganic inert carrier material. In the drug for treating perioperative pain, the adenylyl cyclase inhibitor represented by formula (1) or the pharmaceutically acceptable salt thereof is the only active ingredient. The drug of the present invention can relieve the stresses of undergoing surgery, has a therapeutic effect on pain in the entire perioperative period, and does not have side effects such as addiction.

The application provides a perioperative stress identification method and system based on HRV intelligent monitoring, and relates to the technical field of medical data processing.The method comprises the following steps: determining a segmented period in the perioperative period in which a monitoring period is located; determining a plurality of HRV data and physiological index data, and first input vectors and second input vectors thereof; determining period encoding information according to the segmented period and the starting time of the monitoring period; and further determining a stress index through a stress identification model.According to the application, a plurality of signals of a patient in a perioperative period can be acquired through a wearable physiological signal acquisition device, and the characteristics that an HRV signal can reflect the sympathetic nerve condition are utilized to identify whether the patient has a stress reaction in each segmented period, and a plurality of physiological index data are utilized for auxiliary judgment to improve the accuracy and confidence of identification, and the plurality of acquired data can be continuously acquired and updated to improve the timeliness of identification.