485 results about "Postoperative recovery" patented technology

The invention relates to an orthopedic postoperative drainage liquid infection risk identification method. Drainage liquid is regarded as system output jointly driven by postoperative local immune regulation and wound recovery; capturing a nonlinear time sequence curve; first-order derived trend modeling is carried out; abrupt change after the change rate is stable is analyzed; establishing a postoperative recovery normal path framework, and forming a standard recovery trend library by using drainage fluid dynamic parameters of non-infected cases; comparing the Euclidean offset degree and directional change between the drainage parameter behavior vector of the current patient and the standard trajectory; the change is converted into a visual recovery offset map, and infection prediction data is measured from a multi-day trend angle; constructing and identifying local abnormal signal aggregation; forming a framework of infection event transition to obtain clinical infection nodes of qualitative change caused by quantitative change; according to the method, early-stage accurate recognition can be realized, the intervention opportunity can be obviously advanced, single threshold misjudgment is avoided, the recognition accuracy and specificity are improved, the model adaptability is improved, and the recognition interpretability is enhanced.

The invention relates to the technical field of maxillofacial deformity treatment, and discloses a maxillofacial deformity orthognathic post-operation follow-up visit system and method, the system comprises an image analysis model and a follow-up visit evaluation model, the image analysis model carries out multi-dimensional feature fusion processing on post-operation initial data, and the data comprises three-dimensional bone seam, occlusion function, soft tissue distribution and other feature data; and the follow-up assessment model performs dynamic interference suppression processing on the real-time physiological data stream and then inputs the feature generation layer to simulate a recovery track so as to generate a follow-up assessment instruction. The feature generation layer comprises an image preprocessing module and a dynamic feature generation module, and the dynamic feature generation module is obtained through combined training of multi-type historical postoperative data and real-time physiological parameters and comprises a feature analysis layer, a feature correction layer and an instruction triggering layer. According to the method, the system is applied, and multi-dimensional and intelligent follow-up assessment of postoperative recovery is achieved. According to the method, the accuracy and the real-time performance of follow-up visit are improved, and effective support is provided for postoperative recovery monitoring and intervention.

The invention relates to the technical field of medical instruments, and discloses an angle-adjustable artificial hip joint prosthesis structure which comprises a thighbone connecting assembly, an acetabulum connecting assembly and a movable part movably connected between the thighbone connecting assembly and the acetabulum connecting assembly. The thighbone connecting assembly comprises a first connecting unit fixedly connected with the movable part, a thighbone stem detachably connected to the lower end of the first connecting unit, and a connecting screw fixedly connected to the upper end of the thighbone stem and in threaded connection with the first connecting unit. The acetabulum connecting assembly comprises a second connecting unit fixedly connected with the movable part and an acetabulum fixedly connected to the second connecting unit. Stable rotating connection is achieved through the double-shaft moving part, and a traditional easily-abraded spherical surface structure is replaced; the locking assembly is matched to realize personalized angle adjustment and locking; the femoral stem can be detached and replaced, and adaptability is improved; the surface composite coating promotes osseointegration and improves biocompatibility, the overall structure stability is high, adaptability is high, and postoperative recovery is fast.

The invention relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional operations, which can accurately identify and predict potential complications by performing deep neural network analysis in combination with preoperative medical history, intraoperative real-time physiological data and operation types. It is ensured that a nursing scheme can be finely adjusted based on individual differences of patients, complex physiological data can be processed through a deep neural network, key physiological data are recognized from the complex physiological data, the scheme is dynamically adjusted in the nursing process through a long-short-term memory network, and the nursing accuracy is improved. The change trend of data in the operation is deeply mined, the fluctuation of physiological indexes is tracked, the abnormity is timely identified, the potential risk is predicted, the nursing decision and the physiological state of the patient can be synchronously updated, the working efficiency of nursing personnel is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The invention discloses an integrated management system and method for postoperative care of orthopedic patients, and relates to the technical field of medical treatment. Comprising a bone mineral density dynamic monitoring value, six-dimensional mechanical parameters of a joint movement track, emotion spectrum characteristics in voice interaction, microenvironment temperature and humidity changes collected by wearable equipment and skin surface pressure distribution; inputting the recovery data into a multi-modal decision-making model based on orthopedic biomechanics improvement, and generating a nursing scheme including a skeleton stress safety interval, a virtual rehabilitation scene dynamic parameter and an interdisciplinary intervention priority; the scheme parameters are dynamically optimized through a layered reinforcement learning framework special for the orthopedics department, and the deformation logic of the 3D printing brace and the correction strategy of the nursing robot are synchronously controlled; based on the postoperative complication space-time prediction map, a multidisciplinary collaborative response instruction strictly matched with the rehabilitation stage of the patient is triggered.

Disclosed is an adjustable chair for use during post-surgical recovery, including a seat with an opening adapted to reduce or eliminate pressure on the buttocks and hips when a user is seated.

The invention relates to the technical field of health risk assessment, in particular to a neurosurgery risk prediction method and system based on big data analysis, and the method comprises the steps: obtaining the neural signal intensity of a brain region in preoperative functional image data of a patient, analyzing the balance degree of neural signal transmission, and analyzing the balance of oxygen metabolism distribution according to the nerve conduction rate. And preoperative nerve state information is formed. According to the method, by accurately extracting the preoperative neural activity signals and analyzing the signal transmission delay, the fluctuation amplitude and the oxygen metabolism balance, the accuracy of individual neural function state evaluation is improved. In the postoperative recovery stage, the abnormal region is dynamically recognized in combination with the neural signal change trend, and the metabolism matching capacity is evaluated, so that the recovery mode is more refined. Neural network connection adjustment capability analysis enhances signal transmission stability evaluation, and abnormal region identification accuracy is improved by combining time deviation and oxygen metabolism recovery consistency.

The invention discloses an anorectal postoperative rehabilitation intelligent supervision method and system based on multiple modes, and belongs to the technical field of intelligent supervision. A temperature, humidity, air quality and other multi-mode sensor group is arranged in each anorectal postoperative rehabilitation management inpatient area, the body temperature, heart rate and wound surface images of a patient are synchronously collected, and the wound surface area and seepage color are extracted through image processing; the method comprises the following steps: by taking a time node as a unit, adding a time label to an environment and patient basic data set, constructing a multi-modal comprehensive data set in a unified format, calculating an environment comprehensive index and a physiological comprehensive index, fusing the environment comprehensive index and the physiological comprehensive index to calculate a postoperative rehabilitation risk value, setting a threshold interval to generate low, medium and high three-level risk labels, and the patient risk label set is pushed to the doctor end in real time, a dynamic supervision system is constructed, the anomaly recognition rate and the clinical response speed are improved, the complication occurrence rate is reduced, the rehabilitation period is shortened, and reliable data support is provided for nursing quality improvement and evidence-based medical research.

The invention relates to the technical field of medical care, in particular to a digestive endoscopy postoperative intelligent nursing system based on deep learning. The system comprises an endoscopic postoperative data acquisition and processing module, an endoscopic postoperative feature analysis module, an endoscopic postoperative recovery risk assessment module and a postoperative recovery risk intelligent nursing module, and can acquire physiological data of a patient after a digestive endoscopic surgery and digestive tract state image data after the endoscopic surgery; the long and short time memory network is used for obtaining the long and short time sequence characteristics of the physiological indexes after the endoscopic surgery, the convolutional neural network is used for identifying and obtaining the healing abnormal lesion characteristics after the endoscopic surgery, the characteristics are input into the preset deep neural network model for characteristic fusion, and postoperative recovery risk assessment calculation and postoperative intelligent nursing analysis are carried out. And generating digestive endoscopy postoperative patient recovery nursing suggestions so as to execute corresponding digestive endoscopy postoperative risk recovery nursing operation. According to the invention, postoperative data of the patient can be accurately analyzed, so that nursing decision-making work can be intelligently guided.

The invention discloses a thoracic surgery patient postoperative remote monitoring method and system based on the Internet of Things, and relates to the technical field of medical rehabilitation monitoring. Feature index extraction is carried out by taking body position pressure and respiration collaborative response as a two-factor dynamic evaluation basis, so that high-sensitivity judgment on a thoracic cavity load state is formed; after the abnormal state is recognized, body position adjustment is carried out, acoustic feedback analysis is linked, secondary evaluation after body position adjustment is achieved, intervention effectiveness of body position adjustment is ensured, personalized adjustment suggestions are automatically generated, the whole process of'perception-recognition-execution 'of remote monitoring is opened, the intelligent level and response real-time performance of postoperative recovery management are improved, and the postoperative recovery management efficiency is improved. According to the overall scheme, health risks caused by position misjudgment, intervention lag and monitoring blind areas in a traditional system are effectively avoided.

An embodiment of the present invention discloses an electrocoagulation surgical instrument, which uses a pulling portion and a first operating arm to form a first electrical path, and uses a sheath portion and a second operating arm to form a second electrical path, so as to apply a coagulation current to biological tissue. Thus, on the one hand, the electrocoagulation surgical instrument is configured as a detachable electrocoagulation component and a drive component, which fully utilizes the multiple incisions of laparoscopic surgery, so that the electrocoagulation component and the rod can be respectively inserted into the cavity from different incisions, reducing the size of the wound corresponding to the rod and improving the patient's postoperative recovery speed. On the other hand, during the assembly process of the electrocoagulation component and the drive component, the pulling portion can pull the electrocoagulation component and the drive component toward each other to facilitate the assembly of the two. At the same time, the pulling portion can further pull the first operating arm and the second operating arm closer to each other, so as to realize the electrocoagulation operation of the first operating arm and the second operating arm on the biological tissue, thereby simplifying the surgical operation.

The invention relates to the technical field of intelligent medical treatment, in particular to a urinary surgery postoperative risk layering intelligent nursing management system which comprises the steps of preprocessing dynamic sign flow data of a patient to obtain regular sign time sequence data; and separating a core vital sign track, a wound exudation quantitative sequence and an autonomous perception discomfort record through modal analysis. The feature calculation module compares the vital sign trajectory with a standard recovery trajectory library to generate a sign bias spectrum, analyzes the exudation sequence to obtain a wound humidity distribution vector, and calculates a time attenuation factor of the pain event according to the discomfort record. And the space construction and layering module combines the features to construct a multi-dimensional risk base space, and identifies boundary coordinates of high-risk, medium-risk and low-risk risk clusters through clustering. And the strategy generation module divides risk levels and allocates corresponding monitoring and intervention measures according to the risk levels. According to the system, dynamic and multi-dimensional quantitative evaluation of the postoperative recovery state and objective automatic layering of risks are achieved.

The invention relates to an AI image navigation method, device and equipment for prostatic hyperplasia minimally invasive surgery and a medium thereof. The method comprises the following steps: acquiring a prostate three-dimensional image and an intraoperative real-time image sequence, and fusing the three-dimensional image after preliminary filtering to obtain an optimized and enhanced image; based on the enhanced image and the preoperative three-dimensional image, a three-dimensional offset vector is obtained through a multi-modal registration algorithm combined with an anatomical structure reference, and optimized prostate three-dimensional attitude data is generated in combination with anatomical constraints; combining the attitude data and the three-dimensional image, determining boundary area distribution characteristics, calculating a risk assessment value, mapping a risk level, and generating a path correction instruction to obtain an instrument navigation path if the risk level exceeds a threshold value; and based on the navigation path, constructing a clinical recovery model in combination with the anatomical structure, generating postoperative recovery index simulation data, and performing adjustment and verification until preset requirements are met to obtain a final operation execution scheme. According to the method, precision and individuation of surgical navigation are achieved, and comprehensive technical support is provided for precise implementation of minimally invasive surgery.

The invention discloses a thoracic surgery postoperative drainage monitoring data processing method and a thoracic surgery postoperative drainage monitoring data processing system. The method comprises the following steps: synchronously acquiring thoracic respiration dynamic characteristics of a patient and fluid dynamic characteristics of a thoracic closed drainage system through a data acquisition module; the central processing server establishes a time sequence mapping relationship between the two, performs feature fusion analysis, and calculates to obtain a thoracic cavity-pipeline coupling efficiency index; performing logic judgment on the postoperative recovery state of the patient on the basis of the index, and identifying a chest-pipeline fluid transmission state including breathing work limitation, drainage channel blockage and pleural cavity air leakage; and dynamically generating a grading equipment response strategy including adjusting training intensity and triggering pipeline maintenance early warning or analgesia intervention according to an identification result. According to the method, accurate recognition and closed-loop management of postoperative complications are achieved by quantitatively evaluating the linkage relation between respiration driving and drainage response.

The invention discloses a chest surgery postoperative complication early warning system. The chest surgery postoperative complication early warning system comprises a data acquisition layer, a data transmission layer, a data processing and storage layer, an analysis and early warning layer and a user interface and feedback layer. The data acquisition layer is used for acquiring vital signs of a patient, laboratory inspection, image data and information manually input by medical staff; the data transmission layer transmits the collected data to the data processing and storage layer in real time; the data processing and storage layer preprocesses, stores and manages the collected data; the analysis and early warning layer analyzes the data through a predefined rule and a machine learning model, calculates a risk score in real time, and triggers early warning; and the user interface and feedback layer provides a graphical operation interface, mobile terminal pushing and alarm feedback. According to the invention, the change of the condition of the patient after the thoracic surgery can be accurately monitored in real time, the risk of complication can be early warned in time, decision support is provided for medical personnel, and the postoperative recovery effect of the patient is improved.

The plugging drainage device comprises an outer sleeve, a flushing pipe, an inner suction pipe and an umbrella-shaped plugging mechanism, a plurality of first through holes are formed in the front end of the outer sleeve, the inner suction pipe is arranged in the outer sleeve, a plurality of second through holes are formed in the front end of the inner suction pipe, and the umbrella-shaped plugging mechanism is arranged in the inner suction pipe. The umbrella-shaped plugging mechanism is arranged at the front end of the outer sleeve and can be retracted into the outer sleeve. The device is provided with the plugging mechanism, the fistula can be plugged during flushing, intestinal juice loss is effectively avoided, postoperative recovery of a patient is facilitated, the umbrella-shaped structure is adopted for plugging, compared with bag plugging, the umbrella fabric of the umbrella-shaped structure can be tightly attached to the wound surface, obstruction is effectively avoided, and the application safety of the device is further improved.

The utility model provides an integrated stent-type artificial blood vessel which comprises an artificial blood vessel part comprising an artificial blood vessel main branch used for being arranged corresponding to an ascending aorta of a human body; the covered stent comprises a covered stent trunk and a left subclavian artery branch arranged beside the covered stent trunk and communicated with the covered stent trunk; the bendable connecting tube section is arranged between the artificial blood vessel part and the covered stent, the bendable connecting tube section comprises a main tube section and a side short tubular joint which is arranged on the side of the main tube section and communicated with the main tube section, and in the main blood flow direction of the artificial blood vessel, the near end of the main tube section is connected with the main branch of the artificial blood vessel; the far end of the main pipe section is connected with the near end of the artificial blood vessel main branch, and the axial height of the side short pipe-shaped connector is smaller than that of the left subclavian artery branch. The number of branch arteries needing to be dissociated in an operation is reduced, then dissociation anastomosis time is saved, circulation stopping time is shortened, protection on brain tissue is enhanced, and postoperative rehabilitation of a patient is facilitated.

The invention relates to the technical field of high polymer materials, in particular to biological glue applied to fixation of an esophageal hiatus hernia patch. The biological glue comprises 40 to 60 wt% of fibrinogen, 30 to 50 wt% of a polyethylene glycol polymer, 2 to 8 wt% of an amino-containing small molecule compound, 0.2 to 0.8 wt% of a growth factor and 1 to 3 wt% of glutaraldehyde. The biological glue provided by the embodiment of the invention has excellent mechanical properties and good histocompatibility, and can realize a better patch fixing effect in a hiatus hernia operation, so that postoperative recovery of a patient is guaranteed.

The invention relates to the technical field of sports medicine auxiliary diagnosis, in particular to a rotator cuff tearing recovery evaluation method and system. By combining multiple groups of indexes and image group feature data, the rotator cuff tearing recovery process can be effectively evaluated, score data reflecting the current rotator cuff repair postoperative development state can be obtained, and the postoperative recovery degree and potential risks are more visually determined through the score data. Therefore, automatic evaluation and prediction of the repair process are realized.

The invention discloses a cardiac surgery sternum dilator for preventing rib fracture, which comprises a first distraction arm, a guide plate, a second distraction arm, a distraction plate, a pressure gauge, a brake component and a controller, and is characterized in that the first distraction arm is fixed at one end of the guide plate; the second distraction arm is arranged on the guide plate and can move along the guide plate; guide grooves are formed in the opposite sides of the first distraction arm and the second distraction arm, a distraction plate is inserted into each guide groove, and the distraction plates can move in the length direction and the height direction relative to the guide grooves; the first distraction arm and the second distraction arm are each provided with a pressure gauge in a sliding mode, and the detection ends of the pressure gauges can abut against the corresponding distraction plates. And the brake component is arranged on the second distraction arm. Therefore, the sternum distraction pressure can be detected, braking is carried out when the pressure is too large, and therefore the situation of side injury of rib fracture caused by the too large distraction pressure is avoided, and the discomfort of a patient in the postoperative recovery process is reduced.

The utility model relates to a catheter type ventricular assist system which can provide different flows and is small in trauma, and comprises a single-channel double-cavity cannula and a single-channel single-cavity cannula, the single-channel double-cavity cannula comprises an inner tube and an outer tube, the near end of the inner tube is communicated with an inlet tube of a blood pump, and an outlet tube of the blood pump is communicated with the near end of the outer tube or the near end of the single-channel single-cavity cannula. Blood is sucked in from the blood inflow port at the far end of the inner tube and flows out from the blood outflow port at the far end of the outer tube to form a small-flow circulation auxiliary system, and blood is sucked in from the blood inflow port at the far end of the inner tube and flows out from the opening at the far end of the single-channel single-cavity cannula to form a large-flow circulation auxiliary system. By means of the mode that the outer tube and the single-channel single-cavity cannula are switched, one set of ventricle auxiliary device can meet small-flow circulation assistance and large-flow circulation assistance, and the ventricle auxiliary device is suitable for different scenes. In small-flow circulation assistance, the outer tube and the inner tube are single-channel double-cavity intubation tubes, the single-channel double-cavity intubation tubes can be intervened to the designated position only through one incision, trauma is small, and postoperative recovery is fast.

The present application relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional surgery, in the present application, through the combination of preoperative medical history, intraoperative real-time physiological data and operation type, depth neural network analysis can accurately identify and predict potential complications, and the nursing plan can be adjusted according to the individual differences of patients, the nursing plan can be adjusted according to the individual differences of patients, the depth neural network can process complex physiological data and identify key physiological data, the long short-term memory network can dynamically adjust the scheme in the nursing process, the change trend of intraoperative data is deeply mined, the physiological index fluctuation is tracked, the abnormality is identified in time and the potential risk is predicted, the nursing decision can be updated synchronously with the physiological state of the patient, the working efficiency of the nursing staff is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The invention discloses a pair of binocular visual function training glasses used after strabismus operation, and relates to the technical field of visual rehabilitation training. The interpupillary distance adjusting mechanism is mounted on the upper side of the inner wall of the glasses frame; the two angle adjusting mechanisms are mounted on the two sides of the bottom end of the interpupillary distance adjusting mechanism respectively; the angle adjusting mechanism comprises an adjusting frame, a pitch angle driving assembly, a rotating frame, a lens cone and a miniature display screen. The angle and the position of the visual training pattern displayed by the micro display screen can be dynamically adjusted according to the specific strabismus type and the postoperative recovery condition of a patient, so that the capacity of coordinating the two eyes of the brain visual center is actively exercised and awakened, recovery of the visual functions of the two eyes is promoted, and the recovery effect is improved. By means of the design, the defect of a fixed parameter training lens in the aspect of adaptability is overcome, the binocular cooperation function of the visual center is actively activated through personalized parameter adjustment, and the postoperative binocular fusion capacity and the recovery efficiency of stereoscopic vision are remarkably improved.

The invention relates to the technical field of medical data processing, in particular to a multi-feature recognition based postoperative anesthesia patient state quantitative evaluation method. According to the method, the anesthesia postoperative state is divided into a deep anesthesia stage, a superficial consciousness recovery stage and a cognitive recovery stage based on clinical observation. In the deep anesthesia stage, physiological feature data are collected at high frequency, and a physical sign health index is obtained by calculating the standardized deviation between the physiological feature data and a normal reference value; in the shallow consciousness recovery stage, physiological feature data and unconsciousness behavior data are collected, a weighted model is constructed in combination with the physical sign health index, and an unconsciousness behavior response index is obtained; in the cognitive recovery stage, physiological feature data and subjective feature data are collected, and short-term trend prediction is performed on a cognitive recovery index based on a grey prediction model. Furthermore, multi-source feature data of the three stages are fused to construct a dynamic trajectory prediction model, the postoperative recovery trend and state change of the patient are comprehensively analyzed, and quantitative evaluation of the postoperative delirium risk is achieved.

The invention provides a neurosurgery postoperative nursing information management method. The method comprises the steps that physiological data and nursing operation data of a patient are collected and recorded; processing abnormal values and missing values in the data, standardizing the data and dividing the data into an analysis set and a verification set; training an optimized nursing information management system by using the analysis set, wherein the system adopts an improved intelligent optimization algorithm to adjust parameters of a basic nursing information management model; and inputting the verification set into the trained system to realize effective management. According to the invention, efficient and accurate management of postoperative nursing information can be realized, the nursing work efficiency and quality are improved, and the postoperative recovery effect of a patient is improved.

The invention discloses an intelligent monitoring method and system for postoperative recovery of an orthopedic patient. The method comprises the following steps: acquiring personal information data and postoperative recovery record data of the orthopedic postoperative patient; performing first processing and second processing on the postoperative rehabilitation record data to generate multi-modal rehabilitation data; extracting the multi-mode rehabilitation data, inputting the multi-mode rehabilitation data into an LSTM orthopedic recovery network, and performing model training on the LSTM orthopedic recovery network; using the LSTM orthopedic recovery network to predict the extracted multi-modal rehabilitation data, and generating a prediction result; according to the method, postoperative multi-dimensional data of the orthopedic patient is collected, the richness of the data and the accuracy of subsequent prediction are improved, then the rehabilitation stage of the patient is predicted by adopting the model, and a phased diagnosis report can be generated for the patient.

The invention discloses a gynecological general anesthesia postoperative complication prediction modeling method based on pathological data analysis, and relates to the technical field of postoperative complication prediction, and the method comprises the following steps: collecting preoperative, intraoperative and postoperative multi-dimensional pathological and clinical data of gynecological general anesthesia; establishing a space-time incidence matrix of anxiety psychology, intraoperative pathology and complications; and constructing a gynecological general anesthesia postoperative complication prediction model based on a multi-modal deep learning prediction architecture based on the space-time incidence matrix. Through combination of multi-dimensional data fusion, dynamic correlation analysis and deep learning, transformation from an empirical decision to a data-driven decision is realized. The time-space incidence matrix provides standardized risk assessment logic for doctors; the prediction capability of the model on rare complications fills the prediction blank in a small sample scene. Finally, through real-time risk early warning and individualized intervention suggestions, the safety of the gynecological general anesthesia operation is remarkably improved, the postoperative recovery time of a patient is shortened, and the method has important clinical transformation value.

The invention provides a method and a system for predicting early gastric cancer prognosis by a circulating marker, and relates to the technical field of auxiliary diagnosis. The method comprises the following steps: performing multi-omics detection on a blood sample based on a preset sampling time sequence to obtain a multi-dimensional time sequence characteristic data set containing three groups of heterogeneous data of circulating tumor DNA, exosomes and protein markers; calculating a change slope and a fluctuation variance of the heterogeneous data in adjacent time sequence intervals, constructing a dynamic variation feature matrix in combination with a standard attenuation weighting factor, and deeply mining spatial cross-correlation and sequence dependence features of the matrix to generate a multi-modal fusion feature fingerprint; and performing regression operation on the feature fingerprints by using an integrated learning stack model to obtain a dynamic prognosis risk score, and further retrieving a risk hierarchical mapping table to generate a prognosis evaluation result containing a survival curve. According to the method, multi-modal heterogeneous data can be effectively fused, the biological dynamic characteristics in the tumor postoperative recovery phase are captured, and the accuracy and timeliness of early gastric cancer prognosis prediction are remarkably improved.

The invention is suitable for the technical field of urinary surgery, and particularly relates to a bladder pressure control method and system and transurethral surgery operation equipment. Wherein the bladder environment information comprises a bladder environment model and blood vessel distribution information; the bladder pressure is monitored in real time; wherein the bladder pressure reflects the pressure in the bladder in the operation process; obtaining a perfusion speed and a discharge speed based on the bladder pressure; when a pre-operation instruction is received, the perfusion adjustment speed and the discharge adjustment speed are obtained based on the pre-operation instruction and the bladder environment information; wherein the pre-operation instruction is an instruction which is sent by a doctor and is used for controlling a cutting instrument to cut a tumor or a basal wound surface. According to the bladder pressure control method and system and the transurethral surgery operation equipment provided by the embodiment of the invention, the problem that pressure rise in the bladder causes adverse effects on the safety of a patient and postoperative recovery can be solved.

The invention discloses a 3D printing bone grafting window-free porous tantalum metal interbody fusion cage which comprises a fusion cage body, the fusion cage body is integrally formed by machining medical-grade tantalum metal, and a clamping hole is formed in the front side of the fusion cage body and used for being connected with an operation instrument; the two groups of porous net racks are respectively fixed on the upper surface and the lower surface of the fusion cage body, the outer side surface of each porous net rack is a contact interface, and each contact interface is of an arc-shaped structure; bayonets are symmetrically formed in the inner wall of the front side of the fusion cage body, the clamping hole is formed between the bayonets, and the bayonets are used for limiting operation instruments. The porous tantalum material with high biological activity and high porosity is adopted, reliable spinal fusion can be achieved on the premise that bone grafting is not needed, the problems of bone taking trauma and donor region complications related to bone grafting and immunoreaction caused by allogeneic bone grafting are effectively solved, and therefore the occurrence risk of postoperative complications is reduced, and the bone grafting success rate is increased. The postoperative recovery process of the patient is improved.