Objective To analyze the clinical manifestations of patients over 60 years old with acute respiratory infection in Pudong New Area of Shanghai and the risk factors of positive detection of novel coronavirus, and to provide reference for improving prevention and control strategies and measures. Methods General conditions, clinical features, basic complications and respiratory samples of inpatients over 60 years old with acute respiratory infection from eight hospitals in Pudong New Area of Shanghai from January to October 2023 were collected, and SARS-CoV-2 detection was carried out. Chi-square test and binary logistics regression were used for data analysis. Results A total of 604 patients over 60 years old were collected, including 356 (58.945) males with a median age of 77 (IQR:70-85) years. Of the 604 cases, 264 were detected positive for SARS-CoV-2, with a positive detection rate of 43.71%. The results of univariate analysis showed that there were significant differences in the detection rates of SARS-CoV-2 among different age groups (χ²=10.60, P=0.01) and different months (χ²=87.15, P=0.00), and among those with cough (χ²=5.28, P=0.02), sputum (χ²=4.19, P=0.04), sore throat (χ²=3.93, P=0.04), and hypertension (χ²=7.63, P=0.01). In the binary logistics regression analysis, month (P=0.00, OR=2.93, 95% CI=1.49-5.78) and age (P=0.00, OR=2.60, 95% CI=1.55-4.37) were independent risk factors for positive detection of SARS-CoV-2. Conclusion The majority of hospitalized cases of acute respiratory infection over 60 years old are male, and the risk factors for positive detection of novel coronavirus are age 80~89 years old and time between May and June.

Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective To investigate the correlation of vascular senescence indicators,brachial-ankle pulse wave velocity(baPWV),cardio-ankle vascular index(CAVI),ankle-brachial index(ABI)with total burden of MRI in patients with cerebral small vessel disease(CSVD).Methods A total of 200 CSVD patients admitted to our hospital from November 2023 to October 2024 were retrospectively recruited,and based on their total MRI burden,they were divided into a low-burden group(score:0-1,103 cases)and a high-burden group(score:2-4,97 cases).A athero-sclerosis monitoring device(VS-1500A)was used to detect baPWV,CAVI,and ABI values.The relationships of the three indicators with total MRI burden score and their predictive values for the burden score were analyzed.Results The high-burden group had significantly higher BMI,el-evated homocysteine and uric acid levels,and increased baPWV and CAVI,but lower ABI than the low-burden group(P＜0.01).Multivariate logistic analysis showed that baPWV,CAVI and ABI were independent influencing factors for high MRI burden of CSVD patients.Spearman correlation analysis showed that baPWV and CAVI values were positively correlated(r=0.589,P=0.000;r=0.458,P=0.000),and ABI was negatively correlated with the total MRI burden score of CSVD patients(r=-0.352,P=0.000).ROC curve analysis showed that baPWV(AUC=0.816,P=0.000),CAVI(AUC=0.725,P=0.000)and ABI(AUC=0.676,P=0.000)were all predic-tors for high MRI burden score in CSVD patients.Conclusion baPWV and CAVI are positively,and ABI is negatively correlated with the total MRI burden score of CSVD patients.baPWV,CAVI and ABI show higher predictive value for the high burden score,with baPWV most significant.

Objective:To evaluate the efficacy and safety of Nimotuzumab combined with concurrent chemoradiotherapy in elderly women with locally advanced cervical cancer.Methods:A retrospective analysis was conducted among elderly patients with cervical cancer who received nimotuzumab combined with concurrent chemoradiotherapy in the gynecology department of Beijing Hospital from November 2018 to March 2023.Efficacy assessments included the objective response rate(ORR), recurrence rates after 1-3 years of follow-up, and comparisons of the levels of squamous cell carcinoma antigen(SCC), carcino-embryonic antigen(CEA), and carbohydrate antigen 125(CA125)before and after treatment.Adverse reactions were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events(NCI-CTCAE)version 5.0.Results:A total of 47 elderly patients aged 60 years and older with stage ⅠB3-Ⅳa cervical cancer were included, with ages ranging from 60 to 76 years[mean age: (65.8±4.3) years; median age: 65(62, 70) years].The patients were divided into three age groups: 60-64 years(21 cases), 65-69 years(14 cases), and ≥70 years(12 cases).After treatment, SCC and CEA levels significantly decreased compared to pre-treatment levels, with statistically significant differences ( W=5.281 and 2.607, respectively; both P<0.05).However, there was no significant difference in CA125 levels before and after treatment( W=1.591, P=0.112).Among the 47 patients, 3 did not undergo post-treatment imaging examinations.Efficacy evaluation results were collected from 44 patients, including 21 cases of complete response(CR)(47.7%), 21 cases of partial response(PR)(47.7%), 1 case of stable disease(SD)(2.3%), and 1 case of progressive disease(PD)(2.3%).The ORR was 95.5%(42/44), and the diseae control rate was 97.7%(43/44).There were statistically significant differences in efficacy among different age groups(Fisher's exact test P=0.015).During the treatment process, a total of 36 patients experienced grade 3 or higher adverse reactions during treatment.Among them, 14 cases(29.8%)with grade 3 or higher acute hematological adverse reactions, 11 cases(23.4%)with grade 3 or higher acute gastrointestinal reactions, and 6 cases(12.8%)with grade 3 or higher acute urinary symptoms.Additionally, 2 cases of radiation cystitis and 3 cases of radiation proctitis were reported.There was no statistically significant difference in recurrence rates among different age groups(Fisher's exact test P=0.292).The highest recurrence rate among elderly patients was observed at the 2-3 year follow-up. Conclusions:For elderly patients with good organ function status, standard concurrent chemoradiotherapy combined with nimotuzumab may be an effective treatment for locally advanced cervical cancer.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective:To compare the effect of transcranial magnetic stimulation (rTMS) of the contralesional hemisphere at different frequencies on the recovery of upper limb motor function after a moderate-to-severe ischemic stroke.Methods:The inter-hemisphere compensation model was applied along with electroencephalogram (EEG) power spectrum density measurements. Thirty stroke survivors were randomly assigned to a sham stimulation group ( n=9), a high-frequency stimulation group ( n=11) or a low-frequency stimulation group ( n=10). In addition to physical and pharmacological therapy, the low-frequency and high-frequency groups received 1Hz or 5Hz rTMS, while the sham group received sham stimulation. The rTMS was delivered over the contralesional (unaffected) hemisphere once daily for 20 minutes over 15 consecutive days. Before, as well as 7 and 15 days after the treatment, all of the subjects′ motor functioning was assessed using the Fugl-Meyer Assessment for the upper extremity (FMA-UE) and their ability in the activities of daily living was assessed using the modified Barthel Index (MBI). Resting-state EEGs with the eyes closed were also recorded, and absolute alpha power across the whole brain was calculated. Changes from baseline FMA-UE and MBI scores and absolute alpha power were analyzed using one-way and repeated-measures analysis of variance. Results:After the treatment, significant within-group improvements from baseline were observed in the FMA-UE scores, MBIs and absolute alpha power, except for absolute alpha power in the low-frequency and sham groups. The repeated-measures analysis of variance revealed significant time × group interactions for FMA-UE ( F=9.926, P≤0.001), MBI ( F=8.789, P≤0.001) and absolute alpha power ( F=4.511, P≤0.05). So the treatment effects varied among the groups. Post hoc Bonferroni-corrected comparisons showed that the high-frequency group exhibited significantly greater improvements from baseline in terms of all three indicators compared with the other two groups. Conclusions:High-frequency (5Hz) rTMS applied to the contralesional hemisphere produced greater improvement than low-frequency (1Hz) stimulation in the upper limb motor function of patients with moderate-to-severe stroke. These findings support the use of the interhemispheric compensation model to guide rTMS therapy, particularly for patients with FMA-UE scores below 43.

Objective:To characterize fine motor function in middle-aged and elderly individuals utilizing a novel wearable inertial motion capture device.Additionally, it seeks to investigate the relationship between fine motor deficits and overall cognitive function, as well as various cognitive dimensions.Methods:Participants aged 50 years and older were recruited between November 2022 and April 2023.The Montreal Cognitive Assessment Scale(MoCA)was employed to evaluate the cognitive function of the subjects, and a radar chart was utilized to illustrate the extent of impairment across different cognitive dimensions.An independent computerized fine motor evaluation system was developed using the motion capture technology of a novel wearable microelectromechanical system(MEMS)inertial sensor, enabling a quantitative assessment of fine motor skills.The differences in fine motor function characteristics between the two groups were compared.Spearman's correlation analysis and multivariate logistic regression were conducted to examine the relationship between fine motor deficits and cognitive dysfunction.Results:A total of 289 participants were recruited, among whom 140(48.4%)were classified into the cognitive impairment group.The mean MoCA scores for the cognitive impairment group and the non-cognitive impairment group were 22.2 ± 2.79 and 27.7 ± 1.19, respectively( P<0.001).The electronic assessment of fine motor function revealed that the motion parameters of hand function in the cognitive impairment group were significantly poorer across all three numerical evaluation tasks.Spearman's correlation analysis demonstrated a robust correlation between deficits in fine motor function and cognitive dysfunction.Furthermore, in the multiple logistic regression model, after adjusting for potential confounding factors including age, gender, and education level, a significant association between cognitive dysfunction and fine motor dysfunction persisted. Conclusions:A novel wearable motion capture technology was employed to facilitate the digital assessment of fine motor function.The findings revealed a significant correlation between deficits in fine motor function and cognitive dysfunction among middle-aged and elderly populations.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.