OBJECTIVE To evaluate the efficacy and safety of amoxicillin combined with proton pump inhibitor （PPI） or potassium-competitive acid blocker （P-CAB） for Helicobacter pylori （Hp） eradication. METHODS Randomized controlled trial （RCTs） on amoxicillin combined with PPI or P-CAB for Hp eradication were retrieved from PubMed， Embase， the Cochrane Library， Web of Science， CNKI， Wanfang， and VIP data. The search time frame was from database inception to September 5， 2025. After literature screening， data extraction， and quality assessment， a network meta-analysis was performed using Stata 17.0 software. RESULTS A total of 12 RCTs involving 5 515 patients were included， encompassing 8 therapeutic regimens： PPI combined with high-dose amoxicillin for 14 days （TR1）， PPI combined with low-dose amoxicillin for 14 days （TR2）， P-CAB combined with high-dose amoxicillin for 7 days （TR3）， P-CAB combined with high-dose amoxicillin for 14 days （TR4）， P-CAB combined with high-dose amoxicillin for 10 days （TR5）， P-CAB combined with low-dose amoxicillin for 7 days （TR6）， P-CAB combined with low-dose amoxicillin for 14 days （TR7）， and P-CAB combined with low-dose amoxicillin for 10 days （TR8）. The network meta-analysis results showed that， in terms of intention-to-treat Hp eradication rates， the eradication rates of TR5 and TR4 were significantly higher than those of TR3， TR8， TR6 and TR1 （ P ＜0.05）. The surface under the cumulative ranking curve （SUCRA） values from highest to lowest were： TR4 （89.7%）＞TR5 （82.3%）＞TR7 （71.5%）＞ TR2 （48.6%）＞TR1 （43.9%）＞TR8 （28.7%）＞TR3 （22.7%）＞TR6 （12.6%）. Regarding safety， the incidence of adverse reactions in TR3 and TR5 was significantly lower than that in TR1 （ P ＜0.05）. The SUCRA values from highest to lowest were： TR1 （91.3%）＞TR4 （79.8%）＞TR5 （55.0%）＞TR7 （50.9%）＞TR8 （41.3%）＞TR2 （36.4%）＞TR3 （27.6%） ＞TR6 （17.7%）. CONCLUSIONS Although the regimen of P-CAB combined with high-dose amoxicillin for 14 days demonstrates the best efficacy， the combination of P-CAB with high-dose amoxicillin for 10 days exhibits a better balanced profile in terms of both efficacy and safety.

Objective To investigate the role and potential mechanism of secreted phosphoprotein 1 (SPP1)⁺ macrophages in the formation of chronic renal allograft fibrosis. Methods The expression features of SPP1⁺ macrophages in renal allografts of chronic allograft dysfunction (CAD) patients were analyzed based on single-cell transcriptome data of renal tissues from patients with CAD. Transcription factor VIPER analysis and DoRothEA transcription factor activity analysis were performed on the single-cell transcriptome data. Renal tissue samples were collected from kidney transplant recipients, including the CAD group (n=5) and the non-renal allograft fibrosis group (CTL group, n=5). A mouse model of chronic allograft rejection was established and divided into the allogeneic kidney transplantation group (CAD group, n=3) and the syngeneic kidney transplantation group (SYN group, n=3). Hematoxylin-eosin staining was used to detect renal tissue injury in mice, and Masson staining was used to detect renal tissue fibrosis. Immunofluorescence staining was performed to detect SPP1 expression in renal tissues of transplant recipients and mouse renal allografts. Bone marrow-derived macrophages (BMDMs) were extracted from mice and subjected to hypoxia stimulation. The expression of hypoxia-inducible factor (HIF)-1α and SPP1 was detected by Western blot, and SPP1 expression was detected by flow cytometry. BMDMs were transfected with HIF-1α overexpression plasmid and HIF-1α small interfering RNA (siRNA) followed by hypoxia intervention, and the expression of HIF-1α and SPP1 was detected by Western blot. Mouse aortic endothelial cells (MAECs) were co-cultured with the supernatant of BMDMs, and the expression of endothelial-mesenchymal transition (EndMT)-related markers was detected by Western blot and immunofluorescence. Results Single-cell transcriptome analysis showed that the proportion of SPP1⁺ macrophages in renal allograft tissues was significantly higher in the CAD group than in the CTL group (P<0.05). The renal injury score and the percentage of interstitial fibrotic area in the CAD group were significantly higher than those in the SYN group (both P<0.05). Immunofluorescence staining showed that the proportion of SPP1⁺ macrophages was increased in the CAD group compared with the CTL group, and also increased in the CAD group compared with the SYN group (both P<0.05). VIPER analysis and DoRothEA transcription factor activity analysis revealed activation of the hypoxia pathway and upregulated expression of transcription factors such as HIF-1α in SPP1⁺ macrophages. SPP1 expression was elevated in BMDMs under hypoxic conditions. Knockdown of HIF-1α inhibited hypoxia-induced SPP1 protein expression, whereas overexpression of HIF-1α upregulated SPP1 protein levels. After co-culture of hypoxia-induced BMDMs with MAECs, the expression levels of EndMT-related markers were increased. Conclusions SPP1⁺ macrophages differentiated under hypoxia are significantly infiltrated in the formation of chronic renal allograft fibrosis, and may promote renal allograft fibrosis by inducing EndMT in renal vascular endothelial cells.

Objective: To explore the interaction between school bullying and insomnia in relation to depression-anxiety-stress emotions among primary and secondary school students,so as to provide a basis for preventing negative emotional states in adolescents. Methods: In October 2024, a stratified cluster sampling method was used to select 3 058 students in grade 5-6 of primary, junior and senior high school in Sheyang County of Jiangsu Province. The Delaware Bullying Victimization Scale, Insomnia Severity Index, Depression-Anxiety-Stress Scale-21, and Study Condition Questionnaire were employed to investigate school bullying, insomnia, depression-anxiety-stress emotions, and academic performance. The χ 2 test and Logistic regression were used to analyze the association between school bullying and insomnia interactions and depression-anxiety-stress emotions among primary and secondary school students, multiplicative interaction analysis was conducted, and additive interaction analysis was performed using R software. Results: The detection rates of depression-anxiety-stress emotions among primary and secondary school students were 21.6%, 28.4% and 10.8%, respectively. The detection rates of physical bullying, relationship bullying, verbal bullying and cyberbullying in school bullying were 10.6%, 14.0%, 22.3%, and 6.2%, respectively. The detection rate for insomnia was 23.1%. Results from Logistic regression analysis showed that, after adjusting for relevant factors, physical, relational, verbal, and cyberbullying and insomnia were positively correlated with the detection rates of depression ( OR = 5.72- 10.93), anxiety ( OR =6.35-12.17), and stress emotions ( OR =5.97-14.52) among primary and secondary school students (all P <0.01). The multiplicative interaction between physical, relational, verbal, and cyberbullying and insomnia was positively correlated with the detection rates of depression ( OR =8.00-18.01), anxiety ( OR =11.35-17.76), and stress emotions ( OR =7.64-9.12) in primary and secondary school students (all P <0.01). Additive interactions were observed between physical, relational, verbal, and cyberbullying and insomnia in relation to the detection rates of depression, anxiety, and stress emotions among primary and secondary school students (both RERI and AP >0 and the credible interval excluded 0, SI >1 and the credible interval excluded 1). Conclusion School bullying and insomnia are associated with depression, anxiety, and stress emotions among primary and secondary school students, and they exhibit both multiplicative and additive interactions.

Objective:This study investigates the utility of ultrasound in diagnosing eosinophilic fasciitis (EF).Methods:A retrospective analysis was conducted on the clinical and ultrasound data of 109 EF patients seen at the center between January 1, 2006, and March 31, 2024. The diagnostic efficacy of ultrasound for EF was evaluated by comparing forearm fascia ultrasound findings among EF patients, systemic sclerosis (SSc) patients, and healthy controls (HC).Results:Among the 109 EF patients (male-to-female ratio 2.2︰1), the median age of onset was 36 (29, 48) years, with a median disease duration of 7 (3, 12) months. The study also included 20 SSc patients [median age 49 (35, 61) years] and 20 HC individuals [median age 48 (29, 54) years]. Ultrasound assessments of forearm fascia in EF patients revealed a median fascial thickness of 1.9 (1.4, 2.4) mm. The median fascial thickness was 0.8 (0.7, 0.9) mm in SSc patients and 0.7 (0.5, 0.9) mm in HC individuals. Fascial thickness in EF patients was greater than in SSc ( Z=-11.16, P<0.001) and HC groups ( Z=-11.87, P<0.001). There was a correlation between fascia thickness and C-reactive protein ( r=0.148, P=0.004), erythrocyte sedimentation rate ( r=0.143, P=0.005), and immunoglobulin G ( r=0.120, P=0.020) in EF patients. Receiver operating characteristic (ROC) curve analysis demonstrated a sensitivity of 84.0% and specificity of 95.9% for EF diagnosis, with an area under the curve (AUC) of 0.921 and a cut-off value of 1.005 mm. Conclusion:Ultrasound detection of forearm fascial thickening (>1 mm) aids in diagnosing eosinophilic fasciitis, indicating that ultrasound is a supplementary diagnostic tool for EF.

Objective:To investigate multi-system involvement in Kennedy′s disease and its association with disease progression.Methods:We retrospectively reviewed the clinical, laboratory, and electrophysiological data from 48 genetically confirmed patients with Kennedy′s disease at the Department of Neurology, First Medical Center of the Chinese PLA General Hospital, between February 2016 and February 2024. The disease progression rate was calculated based on the functional scores at baseline and follow-up. Correlation analyses and multiple linear regression models were employed to assess the relationships among clinical variables and to identify potential predictors of disease progression.Results:The age of muscle weakness onset ranged from 16 to 66 years (mean 42±11 years), with a diagnostic delay of 5.0 (3.0, 9.8) years. Lower limb weakness was the most common initial symptom in 72.9% (35/48) of patients, and 37.5% (18/48) exhibited non-motor manifestations prior to the onset of weakness. Core motor manifestations included bulbar weakness (89.6%, 43/48) and symmetric proximal limb weakness (83.3%, 40/48), frequently accompanied by gynecomastia (74.2%, 23/31) and sexual dysfunction (64.6%, 31/48). The median CAG repeat length was 43 (42, 46), which showed a significant negative correlation with the age at onset ( r=-0.406, P=0.004). Patients with CAG repeats > 43 had a higher prevalence of sexual dysfunction. Elevated serum muscle enzymes were observed in 97.9% (47/48), and abnormal sex hormone levels were detected in 81.2% (39/48). Sensory neuropathy was present in 68.1% (32/47), with CAG repeat length inversely correlating with compound muscle action potential (CMAP) amplitudes in the median ( β=-0.29; t=-2.27, P=0.029) and ulnar ( β=-0.22; t=-2.23, P=0.031) nerves. Low-frequency repetitive nerve stimulation (RNS) revealed a decrement in 43.3% (13/30) of patients, most commonly affecting the axillary and spinal accessory nerves. The disease progression rate was 1.3±0.3 (range: 0.5-2.0). Furthermore, serum creatine kinase-MB (CK-MB) levels were negatively correlated with disease progression rate ( r=-0.303, P=0.036). Conclusions:Kennedy′s disease presents with diverse initial manifestations and frequent multi-system involvement. Non-motor manifestations may precede muscle weakness, serving as valuable clues for early diagnosis. Widespread sex hormone abnormalities (particularly testosterone/luteinizing hormone dysregulation) support the role of androgen insensitivity in disease pathogenesis. Sensory neuropathies are frequent and not length-dependent. The presence of decremental responses on low-frequency RNS suggests neuromuscular junction dysfunction, which may underlie motor impairment in patients with Kennedy′s disease. Finally, serum CK-MB may serve as a potential biomarker for disease progression.

Under the background of breaking the " five only" evaluation criteria, continuously optimizing the scientific research performance evaluation system of hospitals to mobilize the enthusiasm and creativity of scientific researchers and guide the direction of scientific research development plays an important role in enhancing the overall scientific research capability of hospitals. Through literature analysis and expert consultation, a certain hospital has constructed a personal scientific research performance evaluation index system for medical staff in tertiary public hospitals, oriented towards innovation quality and member contributions, and began to implement it throughout the hospital in 2021. This index system included four categories of scientific research performance: vertical scientific research projects, academic influence, science and technology awards, and transformation of achievements, with a total of 20 indicators. The annual scientific research performance score of an individual would serve as the basis for the distribution of year-end scientific research performance and an important reference for applying for key and major projects within the hospital. After the application of this evaluation index system, the enthusiasm of medical staff for scientific research has been effectively stimulated. The average individual scientific research performance score increased from 0.974 in 2020 to 1.220 in 2023. All scientific research indicators involved in the evaluation system have shown growth, with a significant increase in high-quality results. This evaluation system can provide a reference for the scientific research performance evaluation of public hospitals under the background of breaking the " five only" evaluation criteria.

Objective:To review the literature on improving patients′medical experience, analyze the current research status in this field, and provide references for enhancing patients′medical experience.Methods:A search was conducted for studies related to improving patients′medical experience published from January 2015 to November 2024 in eight databases, including CNKI and Web of Science. Using software CiteSpace 6.4.R1 and VOSviewer 1.6.19 to analyze publication trends, keyword clustering, existing problems in the process of improving patients′medical experience, and the measures taken.Results:6 507 articles were included, of which 4 452 were in English (68.4%) and 2 055 were in Chinese (31.6%). The annual number of publications showed a nearly linear growth trend ( R2 = 0.983 9). The clustering analysis results indicated that domestic and international research mainly focused on patient-centered diagnostic and treatment systems, behaviors, services, and environments. Existing studies revealed that there were still problems such as long waiting times for appointments and consultations (292 articles), uneven distribution of medical resources (198 articles), and poor doctor-patient communication (155 articles). To improve patients′medical experience, the following intervention measures were proposed: accelerating the medical reform process and strengthening government responsibilities (169 articles); enhancing service concepts and innovating service models (363 articles); optimizing the consultation process and simplifying medical procedures (221 articles); improving the consultation environment and optimizing the facilities in the consultation area (181 articles); and integrating technological advantages to cover the entire medical process (346 articles). Conclusions:Research on improving patients' medical experience was increasingly attracting the attention of more and more scholars. Issues such as low service efficiency, unbalanced resource allocation, and poor doctor-patient communication need to be given special attention. In the future, it is recommended to enhance the experience of patients′ medical experience by strengthening policy and institutional guarantees, accelerating the construction of information technology, improving doctor-patient communication skills and humanistic care, and enhancing the capacity of primary medical services.

Objective:To improve the risk management process for clinical trial projects using healthcare failure mode and effect analysis(HFMEA), for references for enhancing the risk identification and preventing capabilities of drug clinical trial institutions.Methods:From June to December 2022, this study focused on the project management process of a clinical trial centre in a tertiary public hospital. Following HFMEA procedures, a research team was established. Core processes prone to failure modes in the drug clinical trial project management and their potential failure modes were identified through group discussions, literature analysis, the Delphi method, and decision tree analysis. High-risk failure modes were screened via risk assessment, corresponding improvement measures were formulated and performed, and their effectiveness was validated.Results:The study identified 6 main processes, 17 sub-processes, and 102 potential failure modes. Delphi analysis confirmed 88 failure modes, with 19 having a failure risk priority number(RPN)≥8.00. Decision tree analysis identified 16 high-risk failure modes, involving 5 main processes and 10 sub-processes. Targeted improvements, such as adopting standardized hospital contract templates and setting deadlines for final payment settlement, etc., were implemented. One year post-implementation(January 2024), the RPN for all 16 high-risk failure modes were<8.00.Conclusions:HFMEA could help hospital clinical trial institutions comprehensively and systematically identify high-risk failure modes in the project management process, develop targeted improvement measures, and improve the level of drug clinical trial project management.

Objective:To systematically evaluate the fairness of traditional Chinese medicine (TCM) healthcare resource allocation at the prefecture-level in China using the healthcare resource agglomeration degree (HRAD) method, so as to provide empirical evidence for optimizing resource distribution.Methods:Data on TCM healthcare resources (including the number of TCM institutions, public TCM hospitals, TCM hospital beds, and TCM healthcare technicians) were collected from 333 prefecture-level regions in 2023. The HRAD method was employed to assess fairness in geographic allocation (HRAD i) and population-based allocation (HRAD i/PAD i). A multi-indicator comprehensive evaluation was conducted using the entropy weight method to determine weighting coefficients. Results:Significant disparities were observed in the geographic agglomeration of TCM resources (HRAD i) in China. Resource-rich regions (HRAD i>5) were primarily concentrated in eastern and some central-western provinces, while resource-scarce regions (HRAD i<1) were mainly distributed in western, northeastern, and parts of central and eastern provinces. Analysis of population-based fairness (HRAD i/PAD i) revealed that most prefecture-level cities nationwide had ratios<1, with only 8 provinces having more cities with ratios>1 than<1. The comprehensive evaluation showed that top-ranked cities in the east (e.g., Hangzhou, Dongying, Shenzhen), central region (e.g., Taiyuan, Zhengzhou), and west (e.g., Hainan Prefecture, Alxa League) were predominantly core cities or sparsely populated areas. Conclusions:China′s prefecture-level TCM healthcare resource allocation exhibits significant geographic and population-based inequities, with excessive concentration in provincial capitals and developed cities. Urgent strategies are needed to optimize resource allocation, enhance fairness and accessibility, including promoting the decentralization of high-quality resources, strengthening regional collaborative support, enhancing talent attraction in underdeveloped areas, and leveraging information technology to improve efficiency.

Medical record homepage is a core basis for healthcare quality management, medical insurance payment, and public hospital performance evaluation.The completeness and accuracy of its data directly affect the medical quality and economic benefits of hospitals. Since July 2022, a tertiary hospital had built an auxiliary decision-making system for diagnosis omissions based on artificial intelligence technology, which was officially launched in January 2023. The system aimed to improve the quality of data on the first page of medical records and ensure reasonable payment by medical insurance. This system was built on the hospital′s electronic medical records, and integrated natural language processing, medical knowledge graphs and deep learning technologies to create three engines: diagnosis omission recognition, ICD coding and DRG grouping. The diagnosis omission recognition engine identified both explicit and implicit omitted diagnoses by using a context semantic analysis model and a contrastive learning framework for dual judgment. It also interacted with the ICD coding and DRG grouping engines to enhance the accuracy of DRG grouping. Since its launched, the system has achieved remarkable results. A comparative analysis revealed that the rate of missing diagnoses on hospital medical record homepages has decreased from 31.31% during January to September 2022 to 12.34% during the same period in 2023, and the quality control time for a single medical record had been reduced from 20 minutes to 5 minutes. Additionally, a simulation calculation showed that the system-assisted DRG grouping can increase the hospital′s medical insurance surplus. The system could provide reference and guidance for public hospitals in China to improve the quality of the homepage of medical records and better adapt to medical insurance payment reform.