ObjectiveTo investigate the efficacy of sequential tenofovir alafenamide fumarate （TAF） therapy versus the regimen of entecavir （ETV） combined with TAF in chronic hepatitis B （CHB） patients experiencing low-level viremia （LLV） after ETV therapy， as well as their impact on virologic response， liver and renal function， and blood lipid levels. MethodsA total of 217 CHB patients with LLV after ETV treatment who were admitted to Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from May 2020 to December 2023 were enrolled， and according to the treatment regimen， they were divided into TAF group （180 patients receiving sequential TAF therapy） and combined group （37 patients receiving ETV+TAF therapy）. The propensity score matching （PSM） method was used to match the patients at a ratio of 1∶1， and finally 37 patients were included in each group to balance the baseline confounding factors. The two groups were compared in terms of hepatitis B virus DNA （HBV DNA） clearance rate， hepatitis B envelope antigen （HBeAg） clearance rate， liver and renal function parameters （liver stiffness measurement ［LSM］， platelet count ［PLT］， aspartate aminotransferase ［AST］， alanine aminotransferase ［ALT］， and creatinine ［Cr］）， blood lipid levels （total cholesterol ［TC］， triglyceride ［TG］， high-density lipoprotein cholesterol ［HDL-C］， and low-density lipoprotein cholesterol ［LDL-C］）， and the incidence rate of adverse reactions. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the paired t-test was used for comparison within each group； the chi-square test was used for comparison of categorical data between groups. ResultsAfter 48 weeks of treatment， compared with the TAF group， the combined group had significantly higher HBV DNA clearance rate （86.49% vs 59.46%， χ²=6.852， P=0.009） and HBeAg clearance rate （59.46% vs 35.14%， χ²=4.391， P=0.036）. After treatment， compared with the TAF group， the combined group had significantly lower levels of LSM （7.01±1.50 kPa vs 7.90±1.68 kPa， t=2.404， P=0.019）， AST （18.02±2.28 U/L vs 21.12±2.85 U/L， t=5.166， P<0.001）， and ALT （19.85±3.86 U/L vs 22.00±3.90 U/L， t=2.383， P=0.020） and significantly higher levels of PLT ［（218.35±42.60）×10⁹/L vs （192.82±44.13）×10⁹/L， t=2.532， P=0.014］ and Cr （70.92±6.54 μmoL/L vs 67.60±6.13 μmoL/L， t=2.253， P=0.027）. After treatment， there was a slight increase in the level of TC in both the TAF group （5.60±0.89 mmol/L vs 5.18±0.85 mmol/L， t=2.076， P=0.041） and the combined group （5.45±0.80 mmol/L vs 5.02±0.83 mmol/L， t=2.269， P=0.026）. There was no significant difference in the incidence rate of adverse reactions between the TAF group and the combined group （21.62% vs 18.92%， χ²=0.084， P=0.772）. ConclusionFor ETV-treated CHB patients experiencing LLV， compared with sequential TAF therapy， the ETV+TAF combined therapy can effectively increase virologic response rate， alleviate liver fibrosis， and improve liver function， whereas sequential TAF therapy has less impact on renal function. Sequential or combined therapy with TAF may induce a slight increase in the level of TC， which should be taken seriously in clinical practice.

Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

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 evaluate the clinical efficacy of Shenqi Yangxin decoction in the treatment of ischemic cardiomyopathy （ICM） with Qi and Yin deficiency and blood stasis syndrome and its effect on serum hydrogen sulfide （H₂S） and calcium ion （Ca²⁺）. MethodsA total of 64 ICM patients with Qi and Yin deficiency and blood stasis syndrome who met the inclusion criteria were randomly divided into a control group （n=32） and a treatment group （n=32）. All patients received conventional Western medicine treatment. The treatment group was additionally given Shenqi Yangxin decoction. The TCM syndrome score， Minnesota Living with Heart Failure Questionnaire （MLHFQ） score， left ventricular ejection fraction （LVEF）， N-terminal pro-B-type natriuretic peptide （NT-proBNP）， 6-minute walk test （6MWT）， New York Heart Association （NYHA） cardiac function classification， and serum H₂S and Ca²⁺ levels were compared between the two groups pre- and post-treatment. ResultsTwo cases dropped out from each group during the study. Finally， 30 patients in each group were included in the analysis. There were no significant differences in age， gender， course of coronary heart disease， underlying diseases， and laboratory tests between the two groups. Compared with baseline， the TCM syndrome score， MLHFQ score， and NT-proBNP in both treatment group and control group decreased significantly （P<0.01）， LVEF， 6MWT， and H₂S increased significantly （P<0.01）， and serum Ca²⁺ increased （P<0.05）. Compared with the control group after treatment， the MLHFQ score and NT-proBNP in the treatment group decreased （P<0.05）， the TCM syndrome score decreased significantly （P<0.01）， LVEF， 6MWT， and serum Ca²⁺ increased （P<0.05）， and H₂S increased significantly （P<0.01）. The improvement degree of the NYHA cardiac function classification in the treatment group was higher than that in the control group， but there was no significant difference. ConclusionShenqi Yangxin decoction is effective in treating ICM patients with Qi and Yin deficiency and blood stasis， which could significantly improve cardiac function and quality of life， and its therapeutic effect may be related to the regulation of serum H₂S and Ca²⁺ levels.

ObjectiveTo analyze the application trends and research hotspots of action observation therapy (AOT) in the field of stroke rehabilitation over the past decade. MethodsLiteratures on AOT in stroke rehabilitation published from January, 2016 to December, 2025 were retrieved from the Web of Science Core Collection database. CiteSpace 6.4.R1 was used for visual analysis. ResultsA total of 463 articles were included. The annual publication volume showed a fluctuating upward trend. The country with the highest number of publications was China, the most productive institution was Chang Gung University and Consiglio Nazionale delle Ricerche, and the most prolific author was Avanzini Pietro. Mirror neuron system, motor imagery, upper limb and facilitation were identified as high-frequency keywords and bursting words. ConclusionIn the past decade, the number of publications on AOT in stroke rehabilitation has generally increased. Researches are focusing on the synergy of sensory-closed-loop multimodal technologies, reconstruction of fine upper limb function and neural facilitation mechanisms.

Objective To explore the risk factors for mineral and bone disorder in maintenance hemodialysis patients, and to construct and validate a nomogram prediction model. Methods A total of 306 patients undergoing maintenance hemodialysis at Shanghai Eighth People’s Hospital from January 2021 to May 2025 were selected as study subjects and randomly divided into a training set (n＝214) and a validation set (n＝92) in a 7∶3 ratio. In the training set, patients were divided into a normal bone mineral metabolism group and an abnormal bone mineral metabolism group, and related factors were compared between the two groups. The multivariate logistic regression analysis was used to identify the influencing factors of mineral and bone disorder in maintenance hemodialysis patients in the training set, and a nomogram prediction model was constructed. ROC curves were drawn to evaluate the ability of the nomogram model for predicting mineral and bone disorder in these patients. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to analyze the consistency of the predictive probability of nomogram model and actual probability of mineral and bone disorder in these patients. The decision curve was used to assess the clinical benefit using nomogram prediction model. Results Among the 306 hemodialysis patients, 254 patients had mineral and bone disorder, accounting for 83.01%. Among the 214 patients in the training set, 177 had mineral and bone disorder, accounting for 82.71%. In the training set, age, gender, body mass index (BMI), hypertension rate, dialysis age, blood urea nitrogen (BUN), hemoglobin (Hb), albumin (ALB), alkaline phosphatase (ALP), serum creatinine (SCr), uric acid (UA), estimated glomerular filtration rate (eGFR), and rate of taking phosphate binders were statistically significant different between the two groups (P＜0.05). The multivariate logistic regression analysis showed higher age, female, hypertension, longer dialysis duration, decreased eGFR, and not taking phosphate binders were identified as risk factors for mineral and bone disorder in maintenance hemodialysis patients (P＜0.01). The nomogram prediction model was constructed. The area under the ROC curve of the model for mineral and bone disorder in the training set and validation set was 0.895 (95%CI 0.850-0.941) and 0.881 (95%CI 0.830-0.932), respectively, with maximum Youden indice of 0.650 and 0.600, sensitivity of 0.856 and 0.849, and specificity of 0.794 and 0.751. The Hosmer-Lemeshow test showed the nomogram prediction model had good consistency in predictive probabilities with actual probabilities in training set and validation set. The decision curve showed the nomogram model could bring clinical net benefits when the threshold probabilities in the training set and validation set were less than 0.96 and 0.91. Conclusions The nomogram prediction model constructed based on six independent risk factors including age, gender, hypertension, dialysis duration, eGFR, and using phosphate binders or not, shows good discrimination and calibration, with good clinical predictive ability, which could provide guidance for the management of maintenance hemodialysis patients.

Objective To explore the impact of wearable devices in assisting disease monitoring on heart-focused anxiety in patients with tachyarrhythmias. Methods A cross-sectional study design was conducted. 305 patients with tachyarrhythmias who attended the department of cardiology of Zhongshan Hospital, Fudan University in Shanghai from July 2025 to December 2025 were enrolled as the research subjects, and clinical data of patients were collected. Univariate analysis and multiple stepwise regression analysis were used to analyze the impact of wearable devices in assisting disease monitoring on patients’ heart-focused anxiety. Results The mean score of heart-focused anxiety in the 305 patients with tachyarrhythmias was 33.16±9.70. Among them, 104(34.10%) patients used wearable devices in assisting disease monitoring. The results of univariate analysis and multiple stepwise regression showed that the use of wearable devices in assisting disease monitoring was an influencing factor for heart-focused anxiety (P＜0.05), and the patients who used wearable devices in assisting disease monitoring had a significantly lower level of heart-focused anxiety (P＜0.05). Conclusions The use of wearable devices in assisting disease monitoring is associated with a lower level of heart-focused anxiety in patients with tachyarrhythmias. Medical staff can guide patients to rationally use wearable devices in assisting disease monitoring on the basis of evaluating their needs and device operation capabilities.

Objective To explore the safety and feasibility of 5G remote robot-assisted thoracoscopic anatomic lobectomy and segmentectomy. Methods A retrospective analysis was conducted on patients who underwent 5G remote robot-assisted thoracoscopic anatomic lobectomy or segmentectomy between July and September 2024. The surgeries were performed collaboratively by Shanghai Chest Hospital, Affiliated Hospital of Yangzhou University, and The First Affiliated Hospital of Nanchang University. Perioperative outcomes were recorded and analyzed. Results Ten patients were included, comprising 4 anatomic lobectomies and 6 segmentectomies. The median age was 61.0 (56.0, 72.0) years. The median intraoperative bi-directional network latency was 52.5 (39.0, 54.0) ms. There were no instances of network interruption, robot-related adverse events, or conversions to open thoracotomy. The median postoperative chest tube drainage volume was 500.0 (375.0, 600.0) mL, and the median hospital stay was 5.5 (4.0, 6.0) days. No complications of Clavien-Dindo grade Ⅱor higher occurred. All patients were recurrence-free and alive during the 6-month postoperative follow-up period. Conclusion 5G remote robot-assisted thoracoscopic surgery demonstrates high safety and operational stability. This technology shows promising potential for clinical application and is worthy of further development and utilization.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Objective To prepare Zanthoxylum alkaloid thermosensitive hydrogel, optimize the preparation process and conduct related performance studies. Methods Zanthoxylum alkaloids were obtained by reflux extraction, followed by enrichment and purification using macroporous adsorption resin. Poloxamer 407 and Poloxamer 188 were used as substrates to prepare the thermosensitive hydrogel of Zanthoxylum alkaloids, and the preparation process was optimized by orthogonal design. The quality of the hydrogel was systematically evaluated based on its gelation temperature, gelation time, Fourier transform infrared （FTIR） spectroscopy, scanning electron microscopy （SEM） images, mechanical properties, and in vitro release profile. Results The optimal preparation conditions for the Zanthoxylum alkaloid thermosensitive hydrogel were: 20% （g/ml） poloxamer 407, 2% （g/ml） poloxamer 188 and 100 μg/ml Zanthoxylum alkaloid. The gelation temperature was 32.6℃, and the average gelling time was 143.3 s. The hydrogel appeared as a transparent liquid at room temperature and was transformed into a semi-solid gel state when the temperature exceeded 33℃. Experimental results confirmed the successful preparation of poloxamer 407 and poloxamer 188 thermosensitive hydrogel loaded with Zanthoxylum alkaloids, which exhibited good bio adhesion, self-healing properties, and tensile strength. Conclusion The Zanthoxylum alkaloid thermosensitive hydrogel demonstrated favorable mechanical properties and a sustained-release effect, showing promising potential for further development and application.