Objective:To develop an integrated health management system based on wearable devices for conducting health management to discharged patients,so as to improve the lifestyle and medication compliance of patients with cardiovascular and cerebrovascular diseases,and control risk factors of disease,and maintain patients'safety.Methods:The wearable devices,mobile terminals,and hospital's medical information platform were systematically integrated to develop an integrated health management system.A total of 75 patients with cardiovascular and cerebrovascular diseases(coronary heart disease and hypertension)who admitted to the Department of Cardiovascular Medicine of The 940th Hospital of People's Liberation Army Joint Service Support Force during March 1 and April 1,2024 were selected,and they were randomly divided into an intervention group and a control group using the random number table method,with 38 cases in the intervention group and 37 cases in the control group.During the 6 months of intervention observation period after discharge,patients in the intervention group used the integrated health management system for self-health management,while the patients of control group were managed with the conventional mode.The rate of medication compliance,changes of health behaviors,and changes of measurement data of body between the two groups were compared after the intervention.Results:The smoking rate of patients in the intervention group was 18.42%(7/38),which was lower than 43.24%(16/37)of the control group,and the difference was statistically significant(x2=3.94,P<0.05).The average rate of medication compliance of patients in the intervention group was(89.00±2.39)%,which was higher than(84.8±2.37)%of the control group,and the difference was statistically significant(t=2.15,P<0.05).The increase in diastolic blood pressure of patients in the intervention group was(1.76±2.06)mmHg,which was lower than(3.05±1.94)mmHg of the control group,and the difference was statistically significant(t=2.49,P<0.05).Conclusion:The integrated health management system based on wearable devices is effective for the self-management of patients with cardiovascular and cerebrovascular diseases,and it has a good effect in controlling the level of blood pressure,improving behavioral habits,and enhancing medication compliance of patients.

Objective:To investigate the efficacy of anatomical resection (AR) in the early stages of treating solitary hepatocellular carcinoma (HCC) combined with liver cirrhosis with a diameter of ≤5 cm in comparison to different surgical methods of preferential hepatic parenchymal preservation (non-anatomical liver resection, NAR).Methods:The clinical data of 1 390 cases with solitary HCC combined with liver cirrhosis at an early stage who underwent liver resection at Mengchao Hepatobiliary Hospital of Fujian Medical University and six other medical centers from September 2013 to May 2019 were retrospectively analyzed. Patients were divided into the AR group (486 cases) and the NAR group (904 cases) and the wide surgical margin (WSM) group (745 cases) and the narrow surgical margin (NSM) group (645 cases) according to whether they received AR and the width of the surgical margin (1 cm). The basic information of the patients, preoperative evaluation index data, and postoperative follow-up (follow-up every 3 months) were collected. The Kaplan-Meier method was used to plot the survival curve.The log-rank test was used to compare the difference in survival between the two groups. The Cox proportional hazards regression model was used to analyze the factors affecting the prognosis. Propensity score matching (PSM) was applied to reduce intergroup bias.Results:The overall survival (OS) rates for all patients at 1, 3, and 5 years were 95.5%, 79.9%, and 63.5%, respectively. The recurrence-free survival (RFS) rates were 81.5%, 59.0%, and 43.7%, respectively. There was a statistically significant difference in RFS rate between the AR group and the NAR group prior to PSM, but no statistically significant difference in OS rate (RFS rate: 47.0% vs. 41.9%, P<0.05; OS rate: 64.4% vs. 62.9%, P>0.05). The postoperative RFS rate and OS rate were significantly superior in the WSM group than those of the NSM group (RFS rate: 47.8% vs. 37.2%, P<0.001; OS rate: 69.0% vs. 57.3%, P<0.001). There was no statistically significant difference in OS rate and RFS rate between the AR group and the NAR group following PSM (RFS: 46.3% vs. 45.1%, P>0.05; OS rate: 64.0% vs. 64.3%, P>0.05).The 5-year OS and RFS rates in the WSM group were 66.8% and 60.2%, respectively. The 5-year OS and RFS rates for the NSM group were 48.7% and 41.4%, respectively, with a statistically significant difference ( P<0.05). Cox multivariate analysis indicated that serum albumin, tumor diameter, microvascular invasion, and surgical margin were independent prognostic factors affecting OS and RFS. The Child-Pugh grade and satellite lesions were independent prognostic factors affecting OS. Conclusion:Anatomical liver resection is not an independent risk factor for prognosis, but the state of the resection margin determines the prognosis of patients with solitary HCC combined with cirrhosis. Therefore, hepatic resection margins should be prioritized in such patients.

Objective To observe the value of 2D SECara-Net and 3D U2-Net models constructed based on 2D maximal intensity projection(MIP)and 3D time-of-flight MR angiography(3D TOF-MRA)images,respectively,also of their combination for MRA detecting unruptured saccular intracranial aneurysms(USIA).Methods Totally 973 patients with single USIA and 300 subjects who underwent healthy physical examination were retrospectively collected and divided into training set(n=923,containing 723 cases of USIA and 200 healthy subjects)and test set(n=350,containing 250 cases of USIA and 100 healthy subjects)at the ratio of 7:3.Pre-processed 3D TOF-MRA and the obtained 2D-MIP images in training set were imported into 3D U2-Net and 2D SECara-Net models for training and adjusting parameters,respectively.The efficiency of 2 models and their combination for detecting USIA were evaluated.Results The sensitivity,specificity and accuracy of 2D SECara-Net model for detecting USIA in test set was 78.80％(197/250),95.00％(95/100)and 83.43％(292/350),of 3D U2-Net model was 82.80％(207/250),86.00％(86/100)and 83.71％(293/350),respectively.The specificity of 2D SECara-Net model was higher than that of 3D U2-Net model(P=0.030),while no significant difference of sensitivity nor accuracy was found between 2 models(both P＞0.05).The specificity of the combination of the 2 models was 99.00％(99/100),higher than that of 3D U2-Net model(P＜0.05),and the sensitivity and accuracy of the combination was 91.20％(228/250)and 93.43％(327/350),respectivelty,both higher than those of 2 single models(all P＜0.05).Conclusion 2D SECara-Net and 3D U2-Net models had similar,sensitivity and accuracy for MRA detecting USIA.Combination of them could improve the detecting efficacy.

Objective To observe the value of 2D SECara-Net and 3D U2-Net models constructed based on 2D maximal intensity projection(MIP)and 3D time-of-flight MR angiography(3D TOF-MRA)images,respectively,also of their combination for MRA detecting unruptured saccular intracranial aneurysms(USIA).Methods Totally 973 patients with single USIA and 300 subjects who underwent healthy physical examination were retrospectively collected and divided into training set(n=923,containing 723 cases of USIA and 200 healthy subjects)and test set(n=350,containing 250 cases of USIA and 100 healthy subjects)at the ratio of 7:3.Pre-processed 3D TOF-MRA and the obtained 2D-MIP images in training set were imported into 3D U2-Net and 2D SECara-Net models for training and adjusting parameters,respectively.The efficiency of 2 models and their combination for detecting USIA were evaluated.Results The sensitivity,specificity and accuracy of 2D SECara-Net model for detecting USIA in test set was 78.80％(197/250),95.00％(95/100)and 83.43％(292/350),of 3D U2-Net model was 82.80％(207/250),86.00％(86/100)and 83.71％(293/350),respectively.The specificity of 2D SECara-Net model was higher than that of 3D U2-Net model(P=0.030),while no significant difference of sensitivity nor accuracy was found between 2 models(both P＞0.05).The specificity of the combination of the 2 models was 99.00％(99/100),higher than that of 3D U2-Net model(P＜0.05),and the sensitivity and accuracy of the combination was 91.20％(228/250)and 93.43％(327/350),respectivelty,both higher than those of 2 single models(all P＜0.05).Conclusion 2D SECara-Net and 3D U2-Net models had similar,sensitivity and accuracy for MRA detecting USIA.Combination of them could improve the detecting efficacy.

Objective:To develop an integrated health management system based on wearable devices for conducting health management to discharged patients,so as to improve the lifestyle and medication compliance of patients with cardiovascular and cerebrovascular diseases,and control risk factors of disease,and maintain patients'safety.Methods:The wearable devices,mobile terminals,and hospital's medical information platform were systematically integrated to develop an integrated health management system.A total of 75 patients with cardiovascular and cerebrovascular diseases(coronary heart disease and hypertension)who admitted to the Department of Cardiovascular Medicine of The 940th Hospital of People's Liberation Army Joint Service Support Force during March 1 and April 1,2024 were selected,and they were randomly divided into an intervention group and a control group using the random number table method,with 38 cases in the intervention group and 37 cases in the control group.During the 6 months of intervention observation period after discharge,patients in the intervention group used the integrated health management system for self-health management,while the patients of control group were managed with the conventional mode.The rate of medication compliance,changes of health behaviors,and changes of measurement data of body between the two groups were compared after the intervention.Results:The smoking rate of patients in the intervention group was 18.42%(7/38),which was lower than 43.24%(16/37)of the control group,and the difference was statistically significant(x2=3.94,P<0.05).The average rate of medication compliance of patients in the intervention group was(89.00±2.39)%,which was higher than(84.8±2.37)%of the control group,and the difference was statistically significant(t=2.15,P<0.05).The increase in diastolic blood pressure of patients in the intervention group was(1.76±2.06)mmHg,which was lower than(3.05±1.94)mmHg of the control group,and the difference was statistically significant(t=2.49,P<0.05).Conclusion:The integrated health management system based on wearable devices is effective for the self-management of patients with cardiovascular and cerebrovascular diseases,and it has a good effect in controlling the level of blood pressure,improving behavioral habits,and enhancing medication compliance of patients.

Objective:To investigate the efficacy of anatomical resection (AR) in the early stages of treating solitary hepatocellular carcinoma (HCC) combined with liver cirrhosis with a diameter of ≤5 cm in comparison to different surgical methods of preferential hepatic parenchymal preservation (non-anatomical liver resection, NAR).Methods:The clinical data of 1 390 cases with solitary HCC combined with liver cirrhosis at an early stage who underwent liver resection at Mengchao Hepatobiliary Hospital of Fujian Medical University and six other medical centers from September 2013 to May 2019 were retrospectively analyzed. Patients were divided into the AR group (486 cases) and the NAR group (904 cases) and the wide surgical margin (WSM) group (745 cases) and the narrow surgical margin (NSM) group (645 cases) according to whether they received AR and the width of the surgical margin (1 cm). The basic information of the patients, preoperative evaluation index data, and postoperative follow-up (follow-up every 3 months) were collected. The Kaplan-Meier method was used to plot the survival curve.The log-rank test was used to compare the difference in survival between the two groups. The Cox proportional hazards regression model was used to analyze the factors affecting the prognosis. Propensity score matching (PSM) was applied to reduce intergroup bias.Results:The overall survival (OS) rates for all patients at 1, 3, and 5 years were 95.5%, 79.9%, and 63.5%, respectively. The recurrence-free survival (RFS) rates were 81.5%, 59.0%, and 43.7%, respectively. There was a statistically significant difference in RFS rate between the AR group and the NAR group prior to PSM, but no statistically significant difference in OS rate (RFS rate: 47.0% vs. 41.9%, P<0.05; OS rate: 64.4% vs. 62.9%, P>0.05). The postoperative RFS rate and OS rate were significantly superior in the WSM group than those of the NSM group (RFS rate: 47.8% vs. 37.2%, P<0.001; OS rate: 69.0% vs. 57.3%, P<0.001). There was no statistically significant difference in OS rate and RFS rate between the AR group and the NAR group following PSM (RFS: 46.3% vs. 45.1%, P>0.05; OS rate: 64.0% vs. 64.3%, P>0.05).The 5-year OS and RFS rates in the WSM group were 66.8% and 60.2%, respectively. The 5-year OS and RFS rates for the NSM group were 48.7% and 41.4%, respectively, with a statistically significant difference ( P<0.05). Cox multivariate analysis indicated that serum albumin, tumor diameter, microvascular invasion, and surgical margin were independent prognostic factors affecting OS and RFS. The Child-Pugh grade and satellite lesions were independent prognostic factors affecting OS. Conclusion:Anatomical liver resection is not an independent risk factor for prognosis, but the state of the resection margin determines the prognosis of patients with solitary HCC combined with cirrhosis. Therefore, hepatic resection margins should be prioritized in such patients.

Objective To investigate the in vitro anti-inflammatory effects of Sophora davidii Hance leaves total alkaloids(SDLTAs)and possible molecular mechanisms.Methods The lipopolysaccharide(LPS)-induced inflammation model of RAW264.7 cells was used,and different concentrations of SDLTAs(50,100 and 200 μg/mL)were administered,and the effect of SDLTAs on cellular NO expression was detected by the Griess method;ELISA method was used to detect the effect of SDLTAs on the expression of IL-6,TNF-α and IL-1β;The expression of iNOS,NF-κB p65 and IκBα mRNA was detected by RT-qPCR;Western blotting was used to detecte the expres-sion of p-p38,p-p65 and p-JNK in the cells and NF-κB p65 in the nucleus.Results SDLTAs could significantly inhibit the LPS-induced inflammatory response in RAW264.7 cells.SDLTAs significantly decreased the secretion of NO,IL-6,TNF-α and IL-1β in cells(P<0.01),and significantly decreased the mRNA expressions of iNOS,NF-κB p65 and IκBα in cells(P<0.01).Significantly decreased the protein expression of p-p38,p-p65 and p-JNK in cells and NF-κB p65 in nucleus(P<0.01).Conclusion SDLTAs can exert anti-inflammatory effects by regulating the MAPK/NF-κB signalling pathway.

Objective:To design a hospital pre-triage system based on the Spark big data platform and the improved Adaboost algorithm,and to pre-triage patients in the hospital in advance and accelerate the process of medical treatment.Methods:Based on the Spark big data platform,the basic data from patients entering the hospital for the first time was collected in real time,and the blockchain technology was applied to the whole process of data collection,storage and transmission,and the data was analyzed by the improved the Adaboost algorithm.The outpatient data of The 940th Hospital of the PLA Joint Logistics Support Force in the 10 years from 2011 to 2020 were used as the dataset to quickly identify and guide patients to seek medical treatment in the hospital.The application effect of the hospital pre-triage system based on the Spark big data platform and the improved Adaboost algorithm was analyzed.Results:When the custom limit weight threshold of the improved Adaboost algorithm was set to 0.52,the algorithm accuracy reached a peak of 95.56%,and the accuracy of pre-test triage was 4.24%higher than that of the traditional Adaboost algorithm.The average waiting time for patients was shortened from 0.8 h before the triage to 0.5 h,and the average consultation time for patients was shortened from 6 min before the triage to 4.8 min.Conclusion:The hospital pre-triage system based on the big data platform and the improved Adaboost algorithm can pre-triage patients before diagnosis in advance,improve the efficiency and accuracy of the triage,and relieve the hospital visiting pressure.

Objective:To design a medical big data center based on data warehouse(DW)and data service platform,to integrate information resources between different information systems and organizational structures,to build a secure channel for data sharing,and to meet the needs of clinical application data.Methods:Based on data flow direction,and according to hospital clinical services,operation management,and scientific research development,a top-down data application layer,data service layer,DW layer,and operational data storage(ODS)layer design architecture was adopted to design a medical big data center based on DW and data service platform.Guided by hospital data and business,according to the"object-event-report"data splitting logic,the activities corresponding to the roles in each subject domain were disassembled and sorted out to facilitate quick invocation in clinical applications.Results:The medical big data center was equipped with basic modules for patient master index management and master data management,covering 16 major business subject domains and 52 business subdomains,including hospital's clinical services,hospital management,and patient identification.The medical big data center application included clinical data center,operation data center and scientific research data center,and clearly defined the correlation logic between major categories of information,centrally managed the whole life cycle of service application program interfaces,combined master data information,comprehensively managed medical data,realized the normalization of hospital data,and established high-quality data assets and flexible DW models with the help of big data technology.Conclusion:The medical big data center based on DW and data service platform can integrate different information systems of the hospital with data within the hospital,realize the convenient invocation of interface services and the standardized and persistent management of hospital data,and ensure the data applications needs of clinical application,operational decision-making,and scientific research analysis.

In recent years, the artificial intelligence machine learning and deep learning technology have made leap progress. Using clinical decision support system for auxiliary diagnosis and treatment is the inevitable developing trend of wisdom medical. Clinicians tend to ignore the interpretability of models while pursuing its high accuracy, which leads to the lack of trust of users and hamper the application of clinical decision support system. From the perspective of explainable artificial intelligence, the authors make some preliminary exploration on the construction of clinical decision support system in the field of liver disease. While pursuing high accuracy of the model, the data governance techniques, intrinsic interpretability models, post-hoc visualization of complex models, design of human-computer interactions, providing knowledge map based on clinical guidelines and data sources are used to endow the system with interpretability.