Objective: To investigate and analyze the influencing factors and intervention strategy preferences of preoperative dental anxiety in patients undergoing oral implant surgery, and to provide a basis for the clinical formulation and implementation of targeted interventions. Methods: This study was approved by the Hospital Medical Ethics Committee, and written informed consent was obtained from all participants. Using convenience sampling, a cross-sectional survey was conducted from January to October 2025 among 210 patients in the Department of Implantology of a tertiary dental hospital. All participants had been clinically diagnosed and were scheduled to undergo oral implant surgery on the day of the survey. The survey was conducted using a General Information Questionnaire, the Modified Dental Anxiety Scale (MDAS), and an Anxiety Cause Questionnaire. The General Information Questionnaire collected data on patients’ gender, age, presence of systemic diseases, dental treatment history, number of implants, whether bone augmentation was required. The MDAS was used to assess patients’ dental anxiety levels via MDAS scores, with a score ≥ 12 defined as dental anxiety. The Anxiety Cause Questionnaire covered the following items: fear of pain, concern that the instruments might cause permanent damage to their teeth, concern about the dentist’s technique and inability to achieve ideal results, fear of local anesthesia, concern about cross-infection, financial pressure, exposure to an unfamiliar environment and strangers, and previous unpleasant dental experiences. The MDAS scores of the items in the Anxiety Cause Questionnaire and General Information Questionnaire were analyzed using the Mann-Whitney U test or Kruskal-Wallis H test for univariate analysis, and factors with statistical significance in the univariate analysis were further analyzed using binary logistic regression for multivariate analysis. An Intervention Strategy Preference Questionnaire was used to survey patients’ preferences for the following interventions: understanding the surgical procedure, verbal reassurance from medical staff, distraction methods such as listening to music or using stress balls, staying in a physically and mentally relaxing environment, and others. Results: The average preoperative MDAS score of patients undergoing oral implant surgery was 10.91 ± 3.40, and the incidence of dental anxiety (MDAS ≥ 12) was 34.8% (73/210). Univariate analysis showed that female patients, patients aged < 45 years, had significantly higher MDAS scores (P < 0.05). Patients who selected “fear of pain” (79.0%), “fear of local anesthesia” (21.0%), and “exposure to an unfamiliar environment and strangers” (4.8%) as causes of their anxiety had higher MDAS scores than those who did not select these items (P < 0.05). Multivariate logistic regression analysis showed that patient's age (OR = 0.420), fear of pain (OR = 4.234), and exposure to an unfamiliar environment and strangers (OR = 8.220) were independent influencing factors of preoperative dental anxiety in patients undergoing oral implant surgery (P < 0.05). The Intervention Strategy Preference Questionnaire showed that “verbal reassurance from medical staff” (45.2%), “distraction” (43.3%), and “understanding the surgical procedure” (39.5%) were the most preferred intervention strategies among patients. Conclusions Preoperative dental anxiety is common among some patients undergoing oral implant surgery, particularly young and middle-aged patients, those treated by less experienced physicians, and those experiencing anxiety due to a fear of pain or exposure to an unfamiliar environment and strangers. Clinical attention should focus on these patient populations, and systematic preoperative education and psychological counseling should be provided accordingly.

AIM: To explore the risk factors associated with diabetic retinopathy(DR)based on ultra-widefield swept-source optical coherence tomography angiography(UWF-SS-OCTA), and to establish a clinical prediction model.METHODS:A total of 235 patients(235 eyes)with type 2 diabetes mellitus who were treated in the Affiliated Hospital of Xuzhou Medical University from July to November 2024 were selected as the research objects. According to the presence or absence of DR, they were divided into 120 cases(120 eyes)in non-DR group(NDR group)and 115 cases(115 eyes)in non-proliferative DR group(NPDR group). Data on general characteristics, laboratory tests, and OCTA results were collected for both groups. Univariate analysis was employed to identify DR-related risk factors. Logistic regression analysis was conducted to analyze these risk factors and to establish a DR prediction model. The efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve, calibration curve, and decision curve analysis(DCA).RESULTS: The duration of diabetes, fasting blood glucose, blood urea nitrogen(BUN), history of hypertension, and the choroidal vascular index(CVI)were found to be statistically significant in the model(all P<0.05). Specifically, the duration of diabetes, fasting blood glucose, BUN, and history of hypertension were identified as risk factors for DR among diabetic patients, while CVI was recognized as a protective factor. The area under the curve for the model predicting the probability of DR was 0.898(0.859-0.938), with a diagnostic threshold of 0.438. The corresponding sensitivity and specificity were 87.8% and 78.3%, respectively, indicating that the model possesses high predictive value for the occurrence of DR.CONCLUSION: The duration of diabetes, fasting blood glucose, BUN, history of hypertension, and CVI are significantly correlated with DR. The established prediction model demonstrates a substantial screening capability for DR.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion is one of the most commonly used supportive treatments for children with hematological diseases. This guideline provides guidance and recommendations for blood transfusions in children with aplastic anemia, thalassemia, autoimmune hemolytic anemia, glucose-6-phosphate dehydrogenase deficiency, acute leukemia, myelodysplastic syndromes, immune thrombocytopenic purpura, and thrombotic thrombocytopenic purpura. This article presents the evidence and interpretation of the blood transfusion provisions for children with hematological diseases in the "Guideline for pediatric transfusion", aiming to assist in the understanding and implementing the blood transfusion section of this guideline.
Humans ; Child ; Hematologic Diseases/therapy* ; Blood Transfusion/standards* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion for children undergoing hematopoietic stem cell transplantation is highly complex and challenging. This guideline provides recommendations on transfusion thresholds and the selection of blood components for these children. This article presents the evidence and interpretation of the transfusion provisions for children undergoing hematopoietic stem cell transplantation, with the aim of enhancing the understanding and implementation of the "Guideline for pediatric transfusion".
Humans ; Hematopoietic Stem Cell Transplantation ; Child ; Blood Transfusion/standards* ; Practice Guidelines as Topic