Objective: To construct prediction models of female stress urinary incontinence (SUI), and evaluate the efficacy of each model, so as to provide reference for the early diagnosis of SUI. Methods: Female SUI patients treated in our hospital during Oct. 2019 and Oct. 2023 and healthy women undergoing physical examination during the same period were involved. Women 42 days after delivery were included in the postpartum group (n=611), and perimenopausal and postmenopausal women were included in the non-postpartum group (n=409). The number of random seeds was set and the participants were divided into the training and verification sets in a ratio of 7∶3. Relevant clinical data were collected, and meaningful variables were screened using single factor and Lasso regression, which were then incorporated into the K-nearest neighbor method (KNN), support vector machine (SVM)，decision tree (DT) and random forest (RF) algorithms. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) of the models were calculated to screen out the optimal model. Results: There were 352 SUI patients (57.6%) in the postpartum group. According to single factor and Lasso regression, significant variables included age, body mass index (BMI), maximum rapid muscle stage, parity, bladder neck mobility (BND), urethral rotation angle (URA), lateral perineal incision, past incontinence, and constipation. In the verification set, the AUC of KNN，SVM，DT and RF models were 0.881，0.878，0.750 and 0.905,respectively; the AUC, accuracy, F1 index and Kappa value of RF model were the largest. In the non-postpartum group, there were 260 SUI patients, accounting for 63.6%. The significant variables were age，BMI, maximum value and recovery time of fast muscle stage, mean value of slow muscle stage, post-resting stage variability, vaginal delivery, past incontinence, and constipation. In the verification set, the AUC of KNN,SVM，DT and RF models were 0.819,0.805，0.603 and 0.830, respectively; the AUC, accuracy, Kappa value of the RF model were the largest. Conclusion: This study successfully established 4 prediction models for the incidence of SUI in women at 42 days postpartum, perimenopausal and postmenopausal women based on machine learning. Among them, the model adopting the RF algorithm had the best prediction efficiency.

PURPOSE: This study aims to identify the prevalence and risk factors of military training-related abdominal injuries and help plan and conduct training properly. METHODS: This questionnaire survey study was conducted from October 2021 to May 2022 among military personnel from 6 military units and 8 military medical centers and participants' medical records were consulted to identify the training-related abdominal injuries. All the military personnel who ever participated in military training were included. Those who refused to participate in this study or provided an incomplete questionnaire were excluded. The questionnaire collected demographic information, type of abdominal injury, frequency, training subjects, triggers, treatment, and training disturbance. Chi-square test and t-test were used to compare baseline information. Univariate and multivariate regression analyses were used to explore the risk factors associated with military training-related abdominal injuries. RESULTS: A total of 3058 participants were involved in this study, among which 1797 (58.8%) had suffered training-related abdominal injuries (the mean age was 24.3 years and the service time was 5.6 years), while 1261 (41.2%) had no training-related abdominal injuries (the mean age was 23.1 years and the service time was 4.3 years). There were 546 injured patients (30.4%) suspended the training and 84 (4.6%) needed to be referred to higher-level hospitals. The most common triggers included inadequate warm-up, fatigue, and intense training. The training subjects with the most abdominal injuries were long-distance running (589, 32.8%). Civil servants had the highest rate of abdominal trauma (17.1%). Age ≥ 25 years, military service ≥ 3 years, poor sleep status, and previous abdominal history were independent risk factors for training-related abdominal injury. CONCLUSION More than half of the military personnel have suffered military training-related abdominal injuries. Inadequate warm-up, fatigue, and high training intensity are the most common inducing factors. Scientific and proper training should be conducted according to the factors causing abdominal injuries.
Humans ; Military Personnel ; Risk Factors ; Prevalence ; Male ; Abdominal Injuries/etiology* ; Female ; Adult ; Surveys and Questionnaires ; Young Adult

Hospital culture is the sum of common values， codes of conduct， and working methods formed by internal employees within the hospital， and it is the spiritual pillar and core of cohesion of the hospital. Party-building leadership plays an important role in promoting hospital culture construction， including strengthening values guidance， enhancing team cohesion， facilitating management system innovation， and shaping social image and brand value. By analyzing the effectiveness of a series of Party-building activities carried out by Xi’an No. 9 Hospital in recent years， this paper explored the effect and significance of Party-building leadership in promoting hospital culture construction in the new era， as well as proposed guiding strategies for strengthening Party-building work in promoting hospital culture construction in the new era， so as to promote high-quality development of the hospital.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective To evaluate the reliability and validity and perform cost-consequence analysis of the brief version of the Montreal cognitive assessment(MoCA)for identifying cognitive impairment in a community-based population ≥50 years of age.Methods The internal consistency and retest reliability of the brief version of the MoCA were analyzed,and the area under the curve(AUC),sensitivity,and specificity were determined to discriminate mild cognitive impairment(MCI)and dementia with the clinical dementia rating(CDR)as the diagnostic criterion.The consistency between the brief version and the full version was analyzed by the Kappa test and the Bland-Altman method,and the number of individuals entering the diagnostic assessment and the overall assessment time were estimated and compared between the two versions.Results A total of 303 individuals were included in this study,of whom 192,94,and 17 had normal cognitive function,MCI,and dementia,respectively.The Cronbach's α and re-test coefficients of the brief version of MoCA were 0.754 and 0.711(P<0.001),respectively.The brief version showed the AUC,sensitivity,and specificity of 0.889,74.5%,and 93.8% for identifying MCI,and 0.994,100%,and 93.8% for identifying dementia,respectively.When the brief version of MoCA was used to identify 94 patients with MCI in 303 individuals,107 individuals required additional diagnostic assessment,with an overall assessment time of 142.4 h,which represented decreases of 21.3% and 32.7%,respectively,compared with those of the full version.When the brief version of MoCA was used to identify 17 patients with dementia in 303 individuals,35 individuals required additional diagnostic assessment,with an overall assessment time of 70.4 h,a decrease of 29.5% in the time cost compared with the full version.Conclusions The brief version of MoCA can identify cognitively impaired individuals in a community-based middle-aged and elderly population,with diagnostic validity comparable to that of the full version but less time cost and fewer individuals needing additional diagnostic assessment to detect true-positive cases.It could be expanded for use in the community-based primary screening setting.
Humans ; Aged ; Middle Aged ; Cognitive Dysfunction/diagnosis* ; Male ; Female ; Mental Status and Dementia Tests ; Reproducibility of Results ; Dementia/diagnosis* ; Sensitivity and Specificity ; Aged, 80 and over ; Cost-Benefit Analysis

Objective: To delineate the epidemiologic profile of rifampicin resistant pulmonary tuberculosis (RR-PTB) among students in Chongqing, so as to provide evidence for effectively controlling RR-PTB outbreaks in schools. Methods: Individual level surveillance records of 395 student RR-PTB cases reported from 2015 to 2024 were extracted from the China Information System for Disease Control and Prevention. The Joinpoint regression analysis was employed to quantify temporal trends in the registration rate of student RR-PTB cases, and the comparison of RR-PTB registration rates with different demographic characteristics and different regions was performed using Chi-square test. Results: From 2015 to 2024, a total of 395 student RR-PTB cases were identified, with the registration rate ranged from 0.07 per 100 000 to 1.47 per 100 000, showed a fluctuating upward trend ( AAPC= 35.22%, t =4.13, P <0.01). A turning point was detected in 2017, rates rose during 2015-2017 (APC=295.23%， t =4.62， P < 0.01 ) and plateaued thereafter (APC=-0.47%， t =-0.12， P =0.91). The proportion of RR-PTB cases occurring among students increased both among all RR-PTB cases (1.54% in 2015, 7.48% in 2024) and all student pulmonary tuberculosis cases (0.20% in 2015, 7.17% in 2024), with significant linear trends ( χ 2 trend =33.55,159.98, both P <0.01). The majority of cases were enrolled in senior high school (50.38%), classified as retreatment (53.92%), of Han ethnicity (75.95%), and diagnosed with multidrug resistant tuberculosis(53.16%). There were significant differences in the composition of different ethnicity, registration category and resistance pattern between different years( χ 2=23.47, 17.23, 59.64，all P <0.05). The South-Eastern Wuling Mountainous Region exhibited the highest notification rate (3.96 per 100 000), whereas the western region had the lowest rate ( 0.47 per 100 000). County level jurisdictions reported higher rates than district level ones (2.16 per 100 000 vs 0.63 per 100 000 ). Statistically significant differences were observed in the RR-PTB reported rates among students across different districts and counties( χ 2=418.05,167.05,both P <0.01). Conclusions From 2015 to 2024, the registration rate of detected student RR-PTB cases in Chongqing showed an increasing trend. Students have become one of the key populations for drug resistant TB prevention and control. Intensified health education and active case finding should be implemented to enhance proactive surveillance capabilities.

Objective To explore the association between plasma fibrinogen(FBG)levels and the risk of in-hospital mortality among patients with septic shock.Methods The clinical data of 563 patients diagnosed with septic shock in the Intensive Care Unit(ICU)of Shenzhen Second People's Hospital from August 1,2018,to December 31,2020,were collected.Patient demographic information,basic vital signs,and blood routine and biochemical indices upon admission were gathered.Moreover,the Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores were calculated.Binary logistic regression analysis was conducted to explore the correlation between plasma fibrinogen levels and in-hospital mortality in patients with septic shock.Additionally,a generalized additive model(GAM)and smoothed curve fitting were employed to investigate the nonlinear relationship between plasma fibrinogen and in-hospital mortality.Receiver operating characteristic(ROC)curves were constructed for FBG and APACHEⅡ scores to predict in-hospital mortality in septic shock patients.The area under the curve(AUC)was computed to compare the predictive efficacies of the two.Furthermore,a segmented linear regression model was utilized for quantification.Results Binary logistic regression analysis demonstrated a significant negative correlation between plasma fibrinogen levels and in-hospital mortality among patients with septic shock(P<0.05).GAM modeling and smoothed curve fitting disclosed a nonlinear association between plasma fibrinogen levels and in-hospital mortality,with an inflection point at 5.54 g/L.The segmented linear regression model indicated that,to the left of the inflection point(FBG≤5.54 g/L),for every 1 g/L decrease in plasma fibrinogen,the risk of death increased by 24.5%(OR=0.755,P=0.003).Conversely,to the right of the inflection point(FBG>5.54 g/L),the relationship was not statistically significant(OR=1.049,P=0.685).The findings of the subgroup analyses indicated that the characteristics of the subgroups did not alter the relationship between blood fibrinogen levels and in-hospital mortality.Conclusion There is a nonlinear relationship between FBG levels and in-hospital mortality in patients with septic shock,which has predictive value for evaluating the risk of in-hospital mortality in this patient cohort.

Objective:To assess the relationship between basophil levels and mortality in patients with intra-abdominal infection.Methods:Information on patients with intraperitoneal infection admitted to the intensive care unit were extracted from the MIMIC database.A time-dependent Cox regression model was used to adjust for confounders associated with 28-day mortality.Propensity score matching(PSM)was used to balance the baseline differences be-tween groups with different basophil levels,and a restricted cube chart(RCS)was used to show the relationship between basophil count and 28-day mortality in patients with intra-abdominal infection.Results:A total of 4403 patients with intra-abdominal infection were enrolled in the MIMIC database.Patients with high basophil levels have lower mortality than those with low basophil levels.There was an L-shaped curve between basophil level and 28-day mortality,with a cut-off value of 0.47×109/L.Cox regression analysis showed that basophil levels were an independent protective factor for mortal-ity in patients with intra-abdominal infection after adjusting for potential confounders(HR=0.586,95%CI:0.443-0.769).Protective factors for death at basophil levels remained after PSM adjusted for potential confounders(HR=0.628,95%CI:0.470-0.832).Conclusion:Basophil level is an independent protective factor for mortality in patients with intra-abdominal infection,and basophil levels should be dynamically monitored to better evaluate the prognosis of patients.

Objective To study the economic burden caused by healthcare-associated infection(HAI)in patients with severe acute pancreatitis(SAP),and provide theoretical basis for formulating HAI prevention and control measures.Methods Patients with SAP discharged from a tertiary first-class hospital in Jiangxi Province from July 1,2023 to June 30,2024 were selected as the study subjects.Information including demographic characteristics,clinical data,and hospitalization expense were collected.Patients were divided into a HAI group and a non-HAI group according to HAI occurrence.A propensity score matching(PSM)method was used to conduct a 1∶2 ma-tching,and differences in the length of hospital stay and hospitalization expense between the two groups of patients after PSM were compared.Results A total of 709 patients were included in the analysis,out of which 65 cases ex-perienced HAI,with a HAI incidence of 9.17％.After PSM,all 65 patients in the HAI group were successfully matched.The length of hospital stay,total hospitalization expense,expenses of medication and hygiene product of patients in the HAI group were all higher than those in the non-HAI group,and differences were all statistically sig-nificant(all P＜0.001).Patients who experienced≥2 episodes of HAI had a higher economic burden than those who experienced only once(P＜0.05).HAI of bloodstream,abdomen,digestive system,and respiratory system significantly increased the economic burden of patients(all P＜0.05).Conclusion HAI in SAP patients can extend the length of hospital stay and increase economic burden of patients.Targeted infection prevention and control mea-sures should be formulated to reduce the incidence of HAI and save medical resources.