ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

ObjectiveTo investigate the T lymphocyte subset levels and viral loads in newly human immunodeficiency virus (HIV) antibody-confirmed positive cases in Suzhou (2021‒2024), and to analyze potential influencing factors by integrating their demographic characteristics, immune status, and viral replication patterns, thereby providing evidence for HIV/acquired immune deficiency syndrome (AIDS) prevention and control. MethodsPeripheral whole blood samples were collected from newly confirmed HIV-positive cases in Suzhou from 2021 to 2024. T lymphocyte subset analysis and viral load testing were performed, and influencing factors were identified in combination with demographic characteristics. Logistic regression models were employed to identify factors associated with CD4⁺T lymphocyte counts ≤350 cells·μL^-1, and Spearman’s rank correlation test was used to analyze the correlation between logarithmic value of viral load and CD4⁺/CD8⁺ ratio. ResultsAmong the 3 022 confirmed HIV-positive samples, the median CD4⁺T lymphocyte count was 298.00 cells·μL^-1, with 882 cases (29.19%) showing CD4⁺ T lymphocyte counts <200 cells·μL^-1. The median CD8⁺T lymphocyte count was 1 011.00 cells·μL^-1. The median CD4⁺/CD8⁺ ratio was 0.28, with 32.46% of cases exhibiting CD4⁺/CD8⁺ ratios <0.20, and there were statistically significant differences in CD4⁺/CD8⁺ ratio among different genders, age groups, marital status, and sample sources (all P<0.05). Multivariate logistic regression analyses indicated that individuals aged ≥20 years, those who were divorced or widowed, and cases identified through medical institutions had a significantly higher proportion of CD4⁺T lymphocyte counts ≤350 cells·µL⁻¹ compared to those aged <20 years, unmarried individuals, and cases sourced from voluntary counseling and testing (VCT) clinics, respectively. The mean logarithmic value of viral load was (4.29±1.15) copies·mL^-1. The logarithmic value of viral load demonstrated a significantly negative correlation with both CD4⁺/CD8⁺ ratio (r=-0.43, P<0.001) and CD4⁺T lymphocyte count (r=-0.37, P<0.001). ConclusionA substantial proportion of newly diagnosed HIV/AIDS cases in Suzhou are late presenters with high viral load levels. Targeted interventions should prioritize high-risk populations through enhanced active surveillance and the implementation of combined T lymphocyte subsets analysis and viral load testing, which can enable earlier case-finding and timely antiretroviral therapy initiation.

ObjectiveTo explore the incidence of major low anterior resection syndrome （LARS） within six months after sphincter-preserving surgery for rectal cancer and to analyze its associated factors. MethodsClinical records， postoperative rehabilitation data and LARS scores were collected from 889 patients at 3 months postoperatively and from 844 patients at 6 months postoperatively. Patients were divided into a major LARS group and a non-major LARS group. Multivariable Logistic regression was used to analyze factors associated with major LARS at 3 and 6 months postoperatively， and the predictive value of the models was assessed using the Hosmer-Lemeshow goodness-of-fit test and the receiver operating characteristic （ROC）. ResultsAmong patients undergoing sphincter-preserving surgery for rectal cancer， 247 patients （27.8%） had major LARS at 3 months postoperatively and 181 patients （21.4%） at 6 months postoperatively. Multivariable Logistic regression showed that Kegel exercises， preoperative radiotherapy， anastomotic leakage， a tumor distance from the anal verge of ≤5 cm， and an anastomotic distance from the anal verge of ≤5 cm were independent factors for major LARS at 3 months postoperatively （P<0.05）. At 6 months postoperatively， occasional Kegel exercises during 0~3 months， Kegel exercises during 4~6 months， hydrotherapy during 4~6 months， preoperative chemotherapy， a tumor distance from the anal verge of ≤5 cm， and an anastomotic distance from the anal verge of ≤5 cm were independent factors （P<0.05）. The models at 3 and 6 months postoperatively showed goodness-of-fit test P values of 0.986 and 0.517 and area under the curve （AUCs） of 0.843 and 0.870， indicating good predictive value. ConclusionThe incidence of major LARS within six months after sphincter-preserving surgery for rectal cancer is relatively high， and greater attention should be paid to patients who receive preoperative chemoradiotherapy， develop anastomotic leakage， or have tumor and anastomotic distances from the anal verge of ≤5 cm. Patients should also be advised that early postoperative Kegel exercises and hydrotherapy may reduce the incidence of major LARS.

Objective:To understand the prevalence of frailty and the importance of its influencing factors in adult population in Shaanxi Province.Methods:The data were from Shaanxi baseline survey of natural population cohort study in northwest China during 2018-2019. The frailty index (FI) was constructed to evaluate the frailty status of the population, and XGboost model combined with Shapley method was used to analyze the importance of the sociodemographic and life behavior factors affecting the prevalence of frailty by gender and age.Results:A total of 25 079 subjects were included, in whom 964 (3.8%) had frailty, and there was no significant difference in the overall prevalence of frailty between women (3.9%) and men (3.8%) ( P=0.629), but there was a gender specific difference in the distribution of FI ( P<0.001), and the proportion of the pre-frailty in men was higher than that in women. The prevalence of frailty increased with age ( P<0.001), the prevalence of frailty were 1.3%, 2.5% and 7.8% in young, middle-aged and elderly women, respectively, and 1.9%, 2.7% and 5.5% in young, middle-aged and elderly men, respectively. Sociodemographic characteristics and lifestyle patterns were both influencing factors for the prevalence of frailty, but their importance varied with gender and age. The top five contributing factors were education level, staying up late, annual family income level, sedentary time and marital status in young women, and staying up late, smoking, annual family income level, sedentary time and drinking in young men. The top five contributing factors were education level, annual family income level, passive exposure to smoking, staying up late, and sedentary time in middle-aged women, and annual family income level, education level, sedentary time, staying up late and drinking in middle-aged men. The top five contributing factors were annual family income level, passive exposure to smoking, sedentary time, marital status, and smartphone use in elderly women, and education level, annual family income level, smoking, smartphone use and sedentary time in elderly men. Conclusions:There are gender specific differences in the distribution of FI in Shaanxi. The prevalence of frailty increased with age, but young and middle-aged people also have frailty risk. The prevalence of frailty in young men was mainly related to unhealthy life behaviors, such as staying up late, smoking, sedentary behavior and drinking, while the prevalence of frailty in middle-aged and elderly men and women were more affected by sociodemographic factors, such as education level, economic status and marital status.

Objective:Analyze the risk factors for acute lung injury of postoperative acute lung injury(ALI)in patients with Stanford type A aortic dissection(STAAD),and construct a nomogram predictive model.Methods:A retrospective cohort study design was adopted.A total of 112 patients with STAAD who underwent surgical treatment in our hopital from January 2021 to August 2024 were included.They were divided into two groups according to the occurrence of ALI after the surgical:non-ALI group(73 cases)and ALI group(39 cases).Clinical data were collected from both groups of patients.The influencing factors of postoperative ALI in patients with STAAD were analyzed by multivariate logistic regression.Established nomogram prediction model based on influencing factors and validated.Results:Among 112 patients with STAAD who underwent surgical treatment,39 case postoperative ALI occurred,with an incidence rate of 34.82％.Age,preoperative creatinine,body mass index(BMI),preoperative white blood cell count,preoperative lactate and other aspects compared,The difference were statistically significant(P＜0.05).The length of stay in the intensive care unit(ICU)of the ALI group was longer than that of the non ALI group(P＜0.05).The intraoperative red blood cell transfusion volume and extracorporeal circulation time in the ALI group were higher than those in the non ALI group(P＜0.05).Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count were risk factors for postoperative ALI(P＜0.05).The receiver operating characteristic(ROC)curve analysis results show that,the Area under the curve(AUC)of the nomogram prediction model was 0.871.When the optimal critical value was 0.472,its sensitivity and specificity wew 0.887 and 0.776,respectively.The internal validation results of Bootstrap show that,the C-index of the column chart prediction model was 0.862,with an absolute error of 0.032.The calibration curve is close to the ideal curve and the original curve,with a slope close to 1.Conclusions:Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count are independent risk factors for postoperative ALI in patients with STAAD.The nomogram model constructed based on the above risk factors can effectively evaluate the risk of postoperative ALI in patients with STAAD.

Objective:To investigate the diagnostic value of metagenomic next-generation sequencing (mNGS) for pyogenic spinal infections.Methods:A total of 255 patients diagnosed with pyogenic spinal infections were enrolled between September 2022 and September 2024 at Qingdao University Affiliated Hospital, Fuzhou Second General Hospital, First Affiliated Hospital of Nanchang University, Shandong University Affiliated Public Health Clinical Center, and the Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. Among them, 155 were male and 100 were female, with an average age of 62.5±14.2 years (ranging from 13 to 90 years). All patients had samples of infected tissue and/or pus collected for microbial culture and mNGS testing. The number, types, and positive rates of pathogens detected by microbial culture and mNGS were compared. Using culture results as the gold standard, receiver operating characteristic (ROC) curve analysis was performed for mNGS testing and the combined method of mNGS and microbial culture, calculating the area under the curve (AUC) and 95% CI. Results:All 255 cases were clinically diagnosed as pyogenic spinal infections, with 194 cases providing microbiological evidence. The most common Gram-positive bacterium was Staphylococcus aureus, while the most common Gram-negative bacterium was Escherichia coli. A total of 33 pathogenic microorganisms were detected by mNGS, while microbial culture detected 18 pathogenic microorganisms. The positive rate of mNGS was 72.2% (184 out of 255), which was significantly higher than that of 30.2% (77 out of 255) for microbial culture, showing a significant difference (χ 2=90.150, P<0.001); the positive rate of mNGS combined with microbial culture was 76.1% (194 out of 255) with significant difference compared to mNGS alone (χ 2=8.100, P<0.001). Among 178 culture-negative samples, the detection rate of mNGS was 65.7% (117 out of 178); among 77 culture-positive samples, the detection rate of mNGS was 87.0% (67 out of 77), and 97.0% (65 out of 67) of the detected pathogens matched the culture results at the species level. The AUCs of the ROC curves for mNGS testing and the combination of mNGS with microbial culture were 0.606 [95% CI (0.534, 0.678)] and 0.671 [95% CI (0.606, 0.736)], respectively, with significant differences compared to microbial culture ( P=0.007; P=0.007). Conclusions:mNGS demonstrates superior performance over conventional culture in identifying pathogens in pyogenic spinal infections. Moreover, combining mNGS with culture further improves diagnostic yield, supporting its integration into clinical practice.

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]

Inflammatory bowel disease (IBD) is a chronic, nonspecific inflammatory disease of the intestine. In recent years, the treatment goals for IBD have evolved from symptom control and endoscopic remission to histological remission, which is associated with significantly better prognoses. Current parameters for histological evaluation include the Nancy histological index (NHI), Geboes score (GS), Robarts histological index (RHI), and global histological activity score (GHAS). However, the evaluation of clinical histological remission remains limited by the lack of standardized criteria and poor reproducibility, hindering its widespread application. With the development of artificial intelligence (AI) technology, AI tools have been increasingly applied in histological evaluation of IBD and can be integrated with endoscopic and multi-omics approaches. This article reviews the current applications, research progress, and associated challenges of AI in the histological evaluation of IBD.

Objective:To investigate the feasibility and value of nomogram based on base line clinical and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) characteristics for pretreatment predicting the depth of myometrial invasion and tumor grade of endometrioid endometrial carcinoma (EEC).Methods:Preoperative baseline clinical characteristics and DCE-MRI characteristics of 194 EEC patients were prospectively collected at Obstetrics and Gynecology Hospital, Fudan University from October 2020 to January 2022 and used as a training set. Univariate analysis was conducted to compare baseline clinical characteristics and DCE-MRI quantitative parameters [including tumor volume, and mean, median, and standard deviation of volume transfer constant (K trans), rate constant (K ep), extravascular extracellular volume fraction (V e), and initial area under the enhancement curve (iAUC)] between patients with deep myometrial invasion (DMI) and those with superficial myometrial invasion (SMI), as well as between high-grade and low-grade EEC. Multivariate logistics regression analysis was used to identify independent predictors for the construction of nomogram. An independent external testing set comprising 127 EEC patients was retrospectively collected from Zhongshan Hospital, Fudan University and Zhongshan Hospital, Fudan University (Xiamen Branch). The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used for evaluating the model′s predictive performance and clinical net benefit, respectively. Results:(1) The depth of myometrial invasion: univariate analysis showed that in the training set, the EEC patients with DMI differed significantly from those with SMI in clinical characteristics including higher proportion of postmenopausal state and overweight [body mass index (BMI)≥25 kg/m2], and abnormal levels of serum cancer antigen (CA) 125, CA 199, and human epididymis protein 4 (HE4), and in DCE-MRI quantitative parameters including tumor volume, and median, mean, and standard deviation of K trans, median of V e, as well as median, mean, and standard deviation of iAUC (all P<0.05). Multivariate analysis showed that the patient′s menstrual status, BMI, CA 199, tumor volume, and mean of iAUC were independent predictors of the depth of myometrial invasion, and constructed the nomogram (recorded as Nomogram_1), achieving an AUC of 0.861 (95% CI: 0.803-0.919) in the training set. In the independent external testing set, the AUC was 0.876 (95% CI: 0.815-0.938), with corresponding sensitivity of 82.0%, specificity of 80.7%, accuracy of 81.1%, positive predictive value (PPV) of 65.3%, and negative predictive value (NPV) of 91.0% for predicting DMI. (2) The EEC grade: univariate analysis showed that in the training set, high-grade EEC patients differed significantly from low-grade EEC in clinical characteristics including patient′s age, the proportion of postmenopausal state and overweight, and abnormal levels of serum CA 125, and in DCE-MRI quantitative parameters including tumor volume, median, mean, and standard deviation of K trans, median and mean of V e, as well as median, mean, and standard deviation of iAUC (all P<0.05). Multivariate analysis showed that the patient′s menstrual status, BMI, tumor volume, and median of V e emerged as independent predictors of EEC grade, and constructed the nomogram (recorded as Nomogram_2), achieving an AUC of 0.845 (95% CI: 0.786-0.893) in the training set. While in the external testing set, the AUC was 0.819 (95% CI: 0.744-0.894), with corresponding sensitivity of 72.4%, specificity of 72.4%, accuracy of 72.4%, PPV of 43.8%, and NPV of 89.9% for predicting high-grade EEC. (3) The DCA curves demonstrated that both Nomogram_1 and Nomogram_2 yielded obvious positive clinical net benefits across a wide range of threshold probabilities. Conclusion:The nomogram based on pretreatment clinical and DCE-MRI characteristics has the potential to noninvasive predict the depth of myometrial invasion and grade of EEC, providing valuable reference information for clinical management decision-making.

Objective:Taking Inflammatory Bowel Disease(IBD)patients as an example,to explore the impact of disparities in regional outpatient security policies on medication reimbursement benefits for patients,and to provide insights for promoting the reform and development of equal outpatient security policy.Methods:39 cities from 9 provinces in China were selected as research samples to analyze the types,coverage,and benefits of their outpatient security policies.Indicators such as the individual out-of-pocket ratio,deductible,and specified reimbursement rate were used to simulate the actual reimbursement ratio for IBD patients using negotiated drugs.Results:Under the general outpatient coordination policy,the average actual reimbursement rate for medications in IBD patients was 26.36%for residents and 36.47%for employees.Under the outpatient chronic and special disease policy,the average actual reimbursement rate was 42.49%for residents and 50.94%for employees,while patients receiving drug treatment under the outpatient special drug policy have an average actual reimbursement rate of 51.62%(for residents)and 64.92%(for employees).Conclusion:Under China's outpatient security policies,there are significant disparities in reimbursement benefits for IBD patients across different regions.Therefore,it is recommended to strengthen the coordination of outpatient security policies across regions,optimize policy design,and provide patients with more equitable and accessible medical coverage.