Objective To investigate the acceptance and satisfaction of tuberculosis prevention and control personnel in Beijing with the patient management system, and to provide a basis for further improving the patient management model. Methods A survey was conducted on the current usage, satisfaction, willingness to use and system improvement opinions of the patient management system among medical staff involved in the supervision and medication management of pulmonary tuberculosis patients in Beijing. Results A total of 360 medical staff participated in the survey. ^“Patient management^” was the function with the largest number of users, accounting for 96.94%. The proportion of users of each module who believed that the module's design met actual work needs was over 90%. About 94.44% of respondents believed that patient management systems facilitated the transfer and sharing of information between institutions. And 90.83% of respondents thought that the patient management system was easy to operate, and 89.17% of respondents believed that patient management systems reduced workload. About 97.50% of respondents were satisfied with the overall use of the patient management system. The results of the influencing factor analysis showed that those with 3 or less modules designed to meet actual work were less satisfied than those with more than 3 modules, and the difference was statistically significant (P=0.001). Respondents put forward suggestions for improvement on the optimization of operational details such as system response speed, interface design, system login and query statistics. Conclusion Medical staff involved in the follow-up management of pulmonary tuberculosis patients are highly satisfied with their work using the patient management system. During the promotion and use, it is still necessary to continuously optimize the system functions according to work needs so that the system can truly facilitate work.

Objective:To explore the influencing factors for pathological upgrading in prostate cancer patients with a Gleason score of 3 + 3 undergoing targeted biopsy，and to establish a nomogram prediction model.Methods:A retrospective analysis was conducted on 191 patients with localized prostate cancer diagnosed with a Gleason score of 3 + 3 through targeted biopsies at the First Affiliated Hospital of Nanjing Medical University from January 2020 to June 2024. The age of the patients was 67（61，73）years，with prostate-specific antigen（PSA）level of 7.44（5.53，10.19）ng/ml，prostate volume of 35.64（26.59，48.97）ml，and PSA density（PSAD）of 0.20（0.14，0.31）ng/ml 2. Among them，61 cases（31.94%）had a Prostate Imaging Reporting and Data System（PI-RADS）score of 3，104 cases（54.45%）had a score of 4，and 26 cases（13.61%）had a score of 5. The diameter of the main lesion was 10.75（7.86，14.00）mm. The lesions were located in the peripheral zone in 78 cases（40.84%），the transition zone in 99 cases（51.83%），and the anterior fibromuscular stroma in 14 cases（7.33%）. The lesions were found at the apex in 56 cases（29.32%），in the body in 120 cases（62.83%），and at the base in 15 cases（7.85%）. MRI revealed only one lesion with a PI-RADS score ≥ 3 in 131 cases，two suspected lesions in 43 cases，three suspected lesions in 12 cases，and four suspected lesions in 5 cases. Systematic biopsy was positive in 121 cases（63.4%）and negative in 70 cases（36.6%）. The lesions were confined to the left lobe in 63 cases（32.98%），right lobe in 68 cases（35.60%），and involved both lobes in 60 cases（31.41%）. The interval between biopsy and surgery was 9.0（7.0，14.0）days. Univariate analyses were performed using Mann-Whitney U tests or χ2 tests，and multivariate logistic regression was used to identify independent predictors of pathological upgrading. A nomogram model was constructed based on these independent predictors. The model’s discriminative ability was assessed using the area under the receiver operating characteristic（ROC）curve（AUC），and internal validation of the model’s consistency was conducted using the bootstrap resampling method. Decision curve analysis（DCA）was performed to assess clinical utility. Results:Among the 191 cases，60（31.4%）had no pathological upgrading after surgery，while 131（68.6%）showed upgrading. Univariate analysis showed that the maximum diameter of the main lesion［9.0（6.0，13.2）mm vs. 11.0（8.4，14.0）mm］，number of suspicious lesions on MRI［1.0（1.0，1.0）vs. 1.0（1.0，2.0）］，number of positive systematic biopsy cores［1.0（0，2.0）vs. 1.0（0，3.0）］，percentage of positive systematic biopsy cores［0.08（0，0.17）vs. 0.12（0，0.25）］，number of positive targeted biopsy cores［2.0（1.0，3.0）vs. 3.0（1.0，4.0）］，percentage of positive targeted biopsy cores［0.37（0.24，0.75）vs. 0.50（0.38，0.85）］，level of the index lesion，location of the index lesion，and PI-RADS score were associated with pathological upgrading（ P < 0.05）. Multivariate logistic regression analysis showed that PI-RADS score 4（ OR = 5.88，95% CI 2.41 - 14.35），number of suspicious lesions on MRI（ OR = 4.15，95% CI 1.88 - 9.17），location of the index lesion in the transition zone（ OR = 6.86，95% CI 2.81 - 16.73），and percentage of positive targeted biopsy cores（ OR = 4.37，95% CI 1.38 - 14.90）were independent risk factors for pathological upgrading（ P < 0.05）. The nomogram model constructed using these predictors had an AUC of 0.845. Internal validation using the Bootstrap method yielded an AUC value of 0.812，indicating high predictive accuracy of the model. The calibration curve indicated good calibration. Decision curve analysis showed that the threshold range for net benefit in the model was between 12% - 100%. Conclusions:The PI-RADS score 4，the number of lesions with PI-RADS ≥ 3，the location of the main lesion in the transition zone，and the percentage of positive needles in targeted biopsy are independent risk factors for pathological upgrading from Gleason score 3 + 3. The nomogram model constructed from these factors demonstrates good predictive performance and provides a reference for clinical decision-making.

Helicobacter pylori(Hp)is a major pathogen that causes peptic ulcer,mucosa-associated tissue lymphoma and gastric cancer.Adhesion colonization is a prerequisite for the pathogenesis of Hp.After infec-tion,Hp first uses urease to neutralize gastric acid,and then it adapts to the environment through motility and chemotactic swimming of flagella.Finally,Hp adheres to gastric epithelial cells through outer membrane pro-teins.Some outer membrane proteins have the biological effect of transporting virulence factors,mediating in-flammation and assisting Hp to produce pathological changes on human body.This paper reviews the mecha-nism of main colonization factors of Hp.

The Healthy China 2030 Plan set the goal of reducing premature deaths from diabetes by 30% by 2030. However, there has been a lack of assessment of premature mortality for diabetes since the action plan was issued. This study used data from the Global Burden of Disease Study 2021, calculated the premature deaths for diabetes by sex, provinces, and subtypes from 1990 to 2021. We explored the temporal trend of premature mortality using the average annual percent change (AAPC) for different sexes, provinces, and subtypes from 1990 to 2021. Furthermore, we predicted premature mortality for diabetes through 2030 for China and its provinces according to the average annual change rate from 2010 to 2021. There was a first slow upward trend in premature mortality for diabetes from 0.5% in 1990 to 0.6% in 2004, and then a decline until 2021 with premature mortality of 0.4%. By 2030, only Fujian (30.3%) will achieve the desired level of reduction, with only seven provinces meeting the target for females and none for males. There is a large range in the degree of decline between inland and coastal regions, showing obvious geographic differences, and there should be a focus on balancing medical resources.
Humans ; China/epidemiology* ; Female ; Male ; Mortality, Premature/trends* ; Diabetes Mellitus/mortality* ; Goals ; Middle Aged ; Adult

Objective To explore the characteristics and influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery.Methods A retrospective study was performed on ICU patients(n=92,observation group)developing complicated intra-abdominal infection after abdominal surgery versus patients(n=104,control group)without complicated intra-abdominal infection after abdominal surgery in our hospital from January 2020 to December 2023.The characteristics of patients who developed complicated intra-abdominal infections were analyzed and the relevant influencing factors were identified using multivariate Logistic regression analysis.Results A total of 124 strains of pathogenic bacteria were isolated and identified in 92 infected patients,with 64.52％(80/124)of Gram-negative strains comprising mainly 29.03％(36/124)of Escherichia coli,25.81％(32/124)of Gram-positive strains comprising mainly 12.90％(16/124)of Enterococcus faecalis,and 9.68％(12/124)of fungi comprising mainly 6.45％(8/124)of Candida albicans.Multivariate Logistic regression results showed that preoperative underlying disease,surgical methods,duration of surgery,invasive procedures,antibiotic use,and length of ICU stay,enteral nutrition were the influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery(P＜0.0 5).Conclusion Patients with complicated intra-abdominal infection are infected with a variety of pathogenic bacteria,predominantly Gram-negative.The patient's preoperative underlying disease,surgical approach,duration of surgery,invasive procedures,use of antibiotics,length of ICU stay,and early enteral nutrition all affect the risk of complicated intra-abdominal infection in ICU patients after abdominal surgery.

Objective To investigate the prevalence and symptoms of pertussis in patients with cough,and to predict individual risk based on the combination of symptoms.Methods A total of 1 025 patients with cough or contact with pertussis patients were included.Pertussis was confirmed by nasopharyngeal swab PCR.Patients were divided into the juvenile group(278 cases)and the adult group(747 cases)according to age.The duration of cough from onset to study participation,the visual analogue(VAS)score of cough degree and the number of basic symptoms(paroxysmal cough,vomiting after cough,crowing cough,pauses in breathing after cough and fever)were compared between the two groups.The confirmed patients were further grouped by age,and the different symptoms were compared.70%of the sample was used as the training set.Based on the combination of symptoms(paroxysmal cough,post-cough vomiting,chick-crooning cough and pauses in inspirations after coughing),multivariate Logistic regression was used to establish the prediction model and draw the nomogram.30%of the sample was used as the validation set,and the receiver operating characteristic(ROC)curve was drawn.The differentiation of the area under the curve(AUC)evaluation model was calculated.The calibration degree of the model was evaluated by Hosmer-Lemeshow test,and calibration curve was drawn to evaluate the model.Results By PCR,163 cases(15.9%)were confirmed as pertussis.The juvenile group had a longer duration of cough from onset to study participation than the adult group(P＜0.05).The VAS score of cough severity was higher,and the number of basic symptoms of pertussis was more(P＜0.01).In confirmed cases,the proportion of paroxysmal cough,vomiting after cough,crowing cough and inspiratory pause after cough was higher in the juvenile group than that in the adult group(P＜0.01).In the diagnosed cases,the incidence of paroxysmal cough and post-cough vomiting were higher in the＜1-year-old group compared to the 1-9-year-old group and the≥10-year-old group(P＜0.05).The combination of paroxysmal cough,vomiting after cough,crowing cough and inspiratory pause after cough was selected by Logistic regression analysis to establish a nomogram model.The AUC of this model in the training set was 0.852,and the Hosmer-Lemeshow test χ2=0.208,P=0.901,and in the verification set,the AUC was 0.899,and the Hosmer-Lemeshow test χ2=4.202,P=0.122.The predicted value in the calibration curve was very close to the theoretical value in the training set and the verification set,and the fitting degree was high.Conclusion The infection rate of pertussis is high in patients with cough.The nomogram model based on combined symptoms has a better prediction effect on pertussis differentiation,which can provide reference for the monitoring of pertussis.

Objective:To explore the influencing factors for pathological upgrading in prostate cancer patients with a Gleason score of 3 + 3 undergoing targeted biopsy，and to establish a nomogram prediction model.Methods:A retrospective analysis was conducted on 191 patients with localized prostate cancer diagnosed with a Gleason score of 3 + 3 through targeted biopsies at the First Affiliated Hospital of Nanjing Medical University from January 2020 to June 2024. The age of the patients was 67（61，73）years，with prostate-specific antigen（PSA）level of 7.44（5.53，10.19）ng/ml，prostate volume of 35.64（26.59，48.97）ml，and PSA density（PSAD）of 0.20（0.14，0.31）ng/ml 2. Among them，61 cases（31.94%）had a Prostate Imaging Reporting and Data System（PI-RADS）score of 3，104 cases（54.45%）had a score of 4，and 26 cases（13.61%）had a score of 5. The diameter of the main lesion was 10.75（7.86，14.00）mm. The lesions were located in the peripheral zone in 78 cases（40.84%），the transition zone in 99 cases（51.83%），and the anterior fibromuscular stroma in 14 cases（7.33%）. The lesions were found at the apex in 56 cases（29.32%），in the body in 120 cases（62.83%），and at the base in 15 cases（7.85%）. MRI revealed only one lesion with a PI-RADS score ≥ 3 in 131 cases，two suspected lesions in 43 cases，three suspected lesions in 12 cases，and four suspected lesions in 5 cases. Systematic biopsy was positive in 121 cases（63.4%）and negative in 70 cases（36.6%）. The lesions were confined to the left lobe in 63 cases（32.98%），right lobe in 68 cases（35.60%），and involved both lobes in 60 cases（31.41%）. The interval between biopsy and surgery was 9.0（7.0，14.0）days. Univariate analyses were performed using Mann-Whitney U tests or χ2 tests，and multivariate logistic regression was used to identify independent predictors of pathological upgrading. A nomogram model was constructed based on these independent predictors. The model’s discriminative ability was assessed using the area under the receiver operating characteristic（ROC）curve（AUC），and internal validation of the model’s consistency was conducted using the bootstrap resampling method. Decision curve analysis（DCA）was performed to assess clinical utility. Results:Among the 191 cases，60（31.4%）had no pathological upgrading after surgery，while 131（68.6%）showed upgrading. Univariate analysis showed that the maximum diameter of the main lesion［9.0（6.0，13.2）mm vs. 11.0（8.4，14.0）mm］，number of suspicious lesions on MRI［1.0（1.0，1.0）vs. 1.0（1.0，2.0）］，number of positive systematic biopsy cores［1.0（0，2.0）vs. 1.0（0，3.0）］，percentage of positive systematic biopsy cores［0.08（0，0.17）vs. 0.12（0，0.25）］，number of positive targeted biopsy cores［2.0（1.0，3.0）vs. 3.0（1.0，4.0）］，percentage of positive targeted biopsy cores［0.37（0.24，0.75）vs. 0.50（0.38，0.85）］，level of the index lesion，location of the index lesion，and PI-RADS score were associated with pathological upgrading（ P < 0.05）. Multivariate logistic regression analysis showed that PI-RADS score 4（ OR = 5.88，95% CI 2.41 - 14.35），number of suspicious lesions on MRI（ OR = 4.15，95% CI 1.88 - 9.17），location of the index lesion in the transition zone（ OR = 6.86，95% CI 2.81 - 16.73），and percentage of positive targeted biopsy cores（ OR = 4.37，95% CI 1.38 - 14.90）were independent risk factors for pathological upgrading（ P < 0.05）. The nomogram model constructed using these predictors had an AUC of 0.845. Internal validation using the Bootstrap method yielded an AUC value of 0.812，indicating high predictive accuracy of the model. The calibration curve indicated good calibration. Decision curve analysis showed that the threshold range for net benefit in the model was between 12% - 100%. Conclusions:The PI-RADS score 4，the number of lesions with PI-RADS ≥ 3，the location of the main lesion in the transition zone，and the percentage of positive needles in targeted biopsy are independent risk factors for pathological upgrading from Gleason score 3 + 3. The nomogram model constructed from these factors demonstrates good predictive performance and provides a reference for clinical decision-making.

Objective To explore the characteristics and influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery.Methods A retrospective study was performed on ICU patients(n=92,observation group)developing complicated intra-abdominal infection after abdominal surgery versus patients(n=104,control group)without complicated intra-abdominal infection after abdominal surgery in our hospital from January 2020 to December 2023.The characteristics of patients who developed complicated intra-abdominal infections were analyzed and the relevant influencing factors were identified using multivariate Logistic regression analysis.Results A total of 124 strains of pathogenic bacteria were isolated and identified in 92 infected patients,with 64.52％(80/124)of Gram-negative strains comprising mainly 29.03％(36/124)of Escherichia coli,25.81％(32/124)of Gram-positive strains comprising mainly 12.90％(16/124)of Enterococcus faecalis,and 9.68％(12/124)of fungi comprising mainly 6.45％(8/124)of Candida albicans.Multivariate Logistic regression results showed that preoperative underlying disease,surgical methods,duration of surgery,invasive procedures,antibiotic use,and length of ICU stay,enteral nutrition were the influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery(P＜0.0 5).Conclusion Patients with complicated intra-abdominal infection are infected with a variety of pathogenic bacteria,predominantly Gram-negative.The patient's preoperative underlying disease,surgical approach,duration of surgery,invasive procedures,use of antibiotics,length of ICU stay,and early enteral nutrition all affect the risk of complicated intra-abdominal infection in ICU patients after abdominal surgery.

Objective To investigate the prevalence and symptoms of pertussis in patients with cough,and to predict individual risk based on the combination of symptoms.Methods A total of 1 025 patients with cough or contact with pertussis patients were included.Pertussis was confirmed by nasopharyngeal swab PCR.Patients were divided into the juvenile group(278 cases)and the adult group(747 cases)according to age.The duration of cough from onset to study participation,the visual analogue(VAS)score of cough degree and the number of basic symptoms(paroxysmal cough,vomiting after cough,crowing cough,pauses in breathing after cough and fever)were compared between the two groups.The confirmed patients were further grouped by age,and the different symptoms were compared.70%of the sample was used as the training set.Based on the combination of symptoms(paroxysmal cough,post-cough vomiting,chick-crooning cough and pauses in inspirations after coughing),multivariate Logistic regression was used to establish the prediction model and draw the nomogram.30%of the sample was used as the validation set,and the receiver operating characteristic(ROC)curve was drawn.The differentiation of the area under the curve(AUC)evaluation model was calculated.The calibration degree of the model was evaluated by Hosmer-Lemeshow test,and calibration curve was drawn to evaluate the model.Results By PCR,163 cases(15.9%)were confirmed as pertussis.The juvenile group had a longer duration of cough from onset to study participation than the adult group(P＜0.05).The VAS score of cough severity was higher,and the number of basic symptoms of pertussis was more(P＜0.01).In confirmed cases,the proportion of paroxysmal cough,vomiting after cough,crowing cough and inspiratory pause after cough was higher in the juvenile group than that in the adult group(P＜0.01).In the diagnosed cases,the incidence of paroxysmal cough and post-cough vomiting were higher in the＜1-year-old group compared to the 1-9-year-old group and the≥10-year-old group(P＜0.05).The combination of paroxysmal cough,vomiting after cough,crowing cough and inspiratory pause after cough was selected by Logistic regression analysis to establish a nomogram model.The AUC of this model in the training set was 0.852,and the Hosmer-Lemeshow test χ2=0.208,P=0.901,and in the verification set,the AUC was 0.899,and the Hosmer-Lemeshow test χ2=4.202,P=0.122.The predicted value in the calibration curve was very close to the theoretical value in the training set and the verification set,and the fitting degree was high.Conclusion The infection rate of pertussis is high in patients with cough.The nomogram model based on combined symptoms has a better prediction effect on pertussis differentiation,which can provide reference for the monitoring of pertussis.

Objective:To investigate the value of bi-parameter magnetic resonance imaging (bpMRI) in diagnosis and treatment of hematospermia.Methods:The clinical data and bpMRI of 182 patients with hematospermia (hematospermia group) and 51 patients without urinary system diseases (control group) were retrospectively analyzed. Both the control group and the hematospermia group underwent semen quality analysis, blood routine, urine routine, coagulation function, serum PSA test, and bpMRI examination before treatment. There were no significant differences in age [40(33, 50)years vs. 39(31, 53) years, Z=-0.77, P=0.43], body mass index [23.9(22.0, 25.7)kg/m2 vs. 24.5(22.3, 26.1) kg/m 2, Z=-0.50, P=0.62], smoking rate [24.7%(45/182) vs. 27.5%(14/51), χ2=0.16, P=0.69], alcohol consumption rate [29.1%(53/182) vs. 29.4%(15/51), χ2=0.002, P=0.97], and comorbid hypertension [20.9%(38/182) vs. 17.6%(9/51), χ2=0.26, P=0.61] between the hematospermia group and the control group. There was a statistically significant difference in PSA levels between the hematospermia group and the control group [2.82(2.08, 3.68)ng/ml vs 1.59(0.88, 2.28) ng/ml, Z=6.08, P=0.03].The median duration of illness in the hematospermia group was 10(5, 15) months, the median number of red blood cells reported in semen analysis was 17(10, 23)/HP, 59(32.4%) cases had infections in urine routine results, 15(8.2%) cases had infections in blood routine results, and 19(10.4%) cases had coagulation abnormalities. Hematospermia patients can be divided into five categories based on their causes: 105 cases of infection and inflammation, 42 cases of obstruction, 19 cases of tumors, 8 cases of systemic diseases, and 8 cases of iatrogenic factors and trauma. The treatment option was based on etiology: ①Infections, Inflammation, Systemic Diseases, Iatrogenic Factors, and Trauma: Remove the underlying cause and observe or watchful waiting. ②Recurrence of Systemic Diseases, Infections, and Inflammation: Treat the underlying cause with appropriate medication, including nonsteroidal anti-inflammatory drugs (NSAIDs), α-receptor blockers, etc. If there is an infection, administer oral antibiotics for 1-2 weeks. ③Obstruction and Tumors: Perform seminal vesiculoscopy surgery or radical prostatectomy. The efficacy evaluation was porfeomed after 12 months of treatment. Cure: Hematospermia symptoms disappear, with no recurrence. Effective: Symptoms significantly improve, no visible hematospermia, semen analysis shows marked improvement in red blood cells, and neither clinical symptoms nor semen analysis worsen. Not Cured: Visible hematospermia persists, and semen analysis shows no change in red blood cells compared to before treatment. Recurrence: Clinical symptoms improve but significant visible hematospermia reappears, and semen analysis shows red blood cell count >5/HP. Results:The proportion of patients with PI-RADS scores ≥ 3 in the hematospermia group was higher than that in the control group [29.1%(53/182)vs. 13.7%(7/51), χ2=4.94, P=0.03], and the difference was statistically significant. Comparing the imaging characteristics and related parameters of two groups of bpMRI, the results showed that the length and width of the left and right seminal vesicles in the hematospermia group were greater than those in the control group. The length of the left seminal vesicle was [29.9(25.9, 33.4)mm vs. 23.0(21.2, 25.4)mm, Z=7.30, P<0.01], the width of the left seminal vesicle was[20.4(17.8, 23.5)mm vs. 17.2(15.1, 18.5)mm, Z=5.85, P<0.01], the length of the right seminal vesicle was [28.9(24.8, 32.4)mm vs. 23.4(21.5, 28.1)mm, Z=4.68, P<0.01], and the width of the right seminal vesicle was[19.8(17.7, 23.1)mm vs. 17.2(15.1, 18.6)mm, Z=5.45, P<0.01]. The differences were statistically significant. After 12 months of follow-up, 152(83.5%) cases were cured, 21(11.5%) cases were defined as effective, 4(2.2%) cases were not cured, and 5(2.7%) cases had recurrence. Conclusions:The bpMRI examination can clearly identify the location of the hematospermia lesion and the timing of the bleeding. Based on the results of bpMRI, determining the cause and selecting the appropriate treatment strategy is reliable, convenient, and effective.