Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

Objective To observe the effect of tuina on glutamate content and synaptic ultrastructure in spinal dorsal horn of rats with chronic sciatic nerve compression injury;To explore the potential mechanism of tuina regulation of the SNAP25/VGLUT2 pathway in alleviating lumbar disc herniation.Methods A chronic sciatic nerve compression injury model was used to simulate neuropathic pain in lumbar disc herniation.24 SD rats were randomly divided into blank group,model group and tuina group,with 8 rats in each group.From the 4th day after modeling,the tuina group was intervened with the tuina method for 10 minutes once a day for 14 consecutive days.The paw withdrawal threshold(PWT)and paw withdrawal latency(PWL)of rats in each group on the day before modeling,and the 4th,10th,14th and 17th days after modeling were detected.The spinal cord tissue of the modeling side was taken,synaptic ultrastructure of spinal dorsal horn neurons was observed using transmission electron microscopy,immunofluorescence staining was used to detect the expression of NR2A in the spinal dorsal horn,Western blot was used to detect the expression of SNAP25 protein in the spinal dorsal horn,immunohistochemistry was used to detect the expression of VGLUT2 in the spinal dorsal horn,ELISA was used to detect the content of glutamate in the spinal dorsal horn.Results Compared with the blank group,PWT and PWL of the model group were significantly reduced on the 4th,10th,14th and 17th days after modeling(P<0.001),with accumulation of vesicles in the presynaptic membrane of the dorsal horn of the spinal cord,increase in the area of the postsynaptic dense zone,and enlargement of the synaptic cleft,while the protein expressions of NR2A,SNAP25 and VGLUT2 in the spinal dorsal horn increased(P<0.05,P<0.001),and the content of glutamate increased(P<0.001).Compared with the model group,PWT and PWL of the tuina group rats significantly increased on the 10th,14th and 17th days after modeling(P<0.001),synaptic vesicles were evenly distributed,the area of the postsynaptic dense zone decreased,and the synaptic cleft decreased,while the protein expressions of NR2A,SNAP25 and VGLUT2 in the spinal dorsal horn decreased(P<0.05,P<0.001),and the content of glutamate decreased(P<0.01).Conclusion Tuina may regulate the content of glutamate through the SNAP25/VGLUT2 pathway in the spinal dorsal horn,improve the synaptic ultrastructure of neurons,and have an analgesic effect on lumbar disc herniation.

Objective:To investigate the trends in detection, treatment, and outcomes of rifampicin-resistant tuberculosis (TB) in Jiangsu Province from 2013 to 2023, assess the effectiveness of control policies and measures for drug-resistant TB, and provide evidence for better control of drug-resistant TB.Methods:Data and indicators related to the screening, diagnosis, treatment, and outcomes of rifampicin-resistant TB in Jiangsu Province from 2013 to 2023 were obtained from the Tuberculosis Management Information System. The Joinpoint regression method was employed to analyze the trends over this period, and annual percent change (APC) and average annual percent change (AAPC) were calculated. A comparative analysis was also conducted to evaluate the changes before and after implementing relevant policies and measures.Results:From 2013 to 2023, the number of registered rifampicin-resistant TB patients in Jiangsu Province showed a consistent upward trend (APC=AAPC=1.45%, P=0.035). The screening rates for drug resistance among new TB patients in high-risk groups and the proportion of molecular biological testing for drug resistance all exhibited increasing trends, with a notable turning point occurring in 2018. The trend of the treatment enrollment rate for rifampicin-resistant TB patients experienced a significant shift in 2020, showing a marked increase from 2013 to 2020 (APC=12.91%, P=0.008). The treatment success rate of rifampicin-resistant TB patients also showed a significant upward trend after a turning point in 2020 (APC=9.94%, P=0.004). Conclusion:From 2013 to 2023, significant progress was seen in preventing and treating rifampicin-resistant TB in Jiangsu Province, with relevant policies and measures proving to be highly effective.

Objective:To evaluate the utility of ultrasonographic monitoring of the rectus femoris muscle—specifically, the rates of change in thickness and cross-sectional area (CSA)—in assessing nutritional status and long-term functional outcomes in patients with sepsis.Methods:In this prospective observational study, sepsis patients admitted to the ICU of the Second Affiliated Hospital of Soochow University between October 2023 and October 2024 were classified by nutritional status at discharge using the Global Leadership Initiative on Malnutrition (GLIM) criteria. Differences in serial ultrasound-measured rectus femoris thickness and CSA on days 1, 3, 5, and 7 were compared between malnourished and non-malnourished groups. The predictive value of these ultrasound parameters for malnutrition was analyzed. Functional prognosis was assessed using the Sarcopenia Assessment Scale, Short Physical Performance Battery, and Manual Muscle Testing, with correlations to muscle changes examined.Results:Of the 71 enrolled patients (median age 73.00 [ IQR: 61.00–80.00]; 47.89% female, 52.11% male), those with malnutrition showed significantly greater variation rates in rectus femoris thickness and CSA on days 3, 5, and 7 compared to the non-malnourished group ( P < 0.05). ROC analysis revealed that the day-7 CSA variation rate had the highest predictive value for malnutrition (AUC = 0.817, 95% CI: 0.713-0.930). These muscle variation rates also correlated strongly with conventional nutritional markers such as BMI, albumin, and urea. Similarly, patients with impaired functional outcomes exhibited higher variation rates in muscle parameters on days 3, 5, and 7 ( P < 0.05), with the day-7 CSA variation rate being most predictive of functional prognosis (AUC = 0.749, 95% CI: 0.632-0.867). Conclusions:Ultrasonographic assessment of rectus femoris thickness and CSA variation rates provides a valuable tool for evaluating nutritional status and predicting functional prognosis in sepsis patients, outperforming traditional biomarkers. This method shows promise for guiding individualized nutrition support and rehabilitation strategies to improve long-term outcomes.

Objective: To investigate the epidemiological characteristics of pulmonary tuberculosis (PTB) among residents aged 60 years and older in Yangzhou City, Jiangsu Province from 2013 to 2022, so as to provide the evidence for the improvement of PTB prevention and control measures in this population. Methods: Data of PTB cases aged 60 years and older in Yangzhou City from 2013 to 2022 were collected from the Chinese Disease Prevention and Control Information System. The temporal, population, and regional distribution characteristics of PTB cases were analyzed using the descriptive epidemiological method. Results: A total of 8 726 PTB cases aged 60 years and older were registered in Yangzhou City from 2013 to 2022, including 4 167 cases positive for pathogenic tests, with a positive rate of 47.75%. The registered incidence rates and the positive rates of pathogenic tests of PTB among residents aged 60 years and older in Yangzhou City showed downward trends from 2013 to 2022 (both P<0.05). The average annual registered incidence rate of PTB was 83.95/105, and the average annual registered incidence rate of PTB positive for pathogenic tests was 40.09/105. The average annual registered incidence rate of PTB in males was higher than that in females (138.57/105 vs. 31.76/105, P<0.05). The registered incidence rate of PTB showed an increasing trend with age (P<0.05), with the highest rate observed in the age group of 75-<80 years (110.37/105). The top three regions with the highest average annual registered incidence rates of PTB were Jiangdu District (94.34/105), Baoying County (91.61/105) and Hanjiang District (84.93/105). Conclusions The registered incidence of PTB among residents aged 60 years and older in Yangzhou City showed a downward trend from 2013 to 2022. Particular attention should be payed to males, residents aged 75- <80 years, and the elderly in Jiangdu District and Baoying County.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To investigate the trends in detection, treatment, and outcomes of rifampicin-resistant tuberculosis (TB) in Jiangsu Province from 2013 to 2023, assess the effectiveness of control policies and measures for drug-resistant TB, and provide evidence for better control of drug-resistant TB.Methods:Data and indicators related to the screening, diagnosis, treatment, and outcomes of rifampicin-resistant TB in Jiangsu Province from 2013 to 2023 were obtained from the Tuberculosis Management Information System. The Joinpoint regression method was employed to analyze the trends over this period, and annual percent change (APC) and average annual percent change (AAPC) were calculated. A comparative analysis was also conducted to evaluate the changes before and after implementing relevant policies and measures.Results:From 2013 to 2023, the number of registered rifampicin-resistant TB patients in Jiangsu Province showed a consistent upward trend (APC=AAPC=1.45%, P=0.035). The screening rates for drug resistance among new TB patients in high-risk groups and the proportion of molecular biological testing for drug resistance all exhibited increasing trends, with a notable turning point occurring in 2018. The trend of the treatment enrollment rate for rifampicin-resistant TB patients experienced a significant shift in 2020, showing a marked increase from 2013 to 2020 (APC=12.91%, P=0.008). The treatment success rate of rifampicin-resistant TB patients also showed a significant upward trend after a turning point in 2020 (APC=9.94%, P=0.004). Conclusion:From 2013 to 2023, significant progress was seen in preventing and treating rifampicin-resistant TB in Jiangsu Province, with relevant policies and measures proving to be highly effective.

Objective To observe the effect of tuina on glutamate content and synaptic ultrastructure in spinal dorsal horn of rats with chronic sciatic nerve compression injury;To explore the potential mechanism of tuina regulation of the SNAP25/VGLUT2 pathway in alleviating lumbar disc herniation.Methods A chronic sciatic nerve compression injury model was used to simulate neuropathic pain in lumbar disc herniation.24 SD rats were randomly divided into blank group,model group and tuina group,with 8 rats in each group.From the 4th day after modeling,the tuina group was intervened with the tuina method for 10 minutes once a day for 14 consecutive days.The paw withdrawal threshold(PWT)and paw withdrawal latency(PWL)of rats in each group on the day before modeling,and the 4th,10th,14th and 17th days after modeling were detected.The spinal cord tissue of the modeling side was taken,synaptic ultrastructure of spinal dorsal horn neurons was observed using transmission electron microscopy,immunofluorescence staining was used to detect the expression of NR2A in the spinal dorsal horn,Western blot was used to detect the expression of SNAP25 protein in the spinal dorsal horn,immunohistochemistry was used to detect the expression of VGLUT2 in the spinal dorsal horn,ELISA was used to detect the content of glutamate in the spinal dorsal horn.Results Compared with the blank group,PWT and PWL of the model group were significantly reduced on the 4th,10th,14th and 17th days after modeling(P<0.001),with accumulation of vesicles in the presynaptic membrane of the dorsal horn of the spinal cord,increase in the area of the postsynaptic dense zone,and enlargement of the synaptic cleft,while the protein expressions of NR2A,SNAP25 and VGLUT2 in the spinal dorsal horn increased(P<0.05,P<0.001),and the content of glutamate increased(P<0.001).Compared with the model group,PWT and PWL of the tuina group rats significantly increased on the 10th,14th and 17th days after modeling(P<0.001),synaptic vesicles were evenly distributed,the area of the postsynaptic dense zone decreased,and the synaptic cleft decreased,while the protein expressions of NR2A,SNAP25 and VGLUT2 in the spinal dorsal horn decreased(P<0.05,P<0.001),and the content of glutamate decreased(P<0.01).Conclusion Tuina may regulate the content of glutamate through the SNAP25/VGLUT2 pathway in the spinal dorsal horn,improve the synaptic ultrastructure of neurons,and have an analgesic effect on lumbar disc herniation.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.