OBJECTIVE To investigate the risk factors for sodium valproate （VPA）-induced hyperammonemia in neurocritical patients， and to construct a risk prediction model. METHODS Clinical data were retrospectively collected from 172 neurocritical patients who received VPA treatment in the Department of Critical Care Medicine， the Fourth Affiliated Hospital of Soochow University from January 2022 to June 2025. Patients were divided into the hyperammonemia group （73 cases） and the normal group （99 cases） based on their blood ammonia levels. Univariate analysis and LASSO regression analysis were used to screen for predictive variables. Independent factors were identified through multivariate Logistic regression analysis， and a nomogram was constructed accordingly. The performance of the model was evaluated using receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis （DCA）. RESULTS Combination of univariate analysis and LASSO regression analysis screened out seven predictive variables： body mass index （BMI）≥24.0 kg/m 2 ， concomitant use of benzodiazepines， VPA blood concentration， hemoglobin， serum urea， average daily VPA dose， and albumin. Multivariate Logistic regression analysis showed that concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， VPA blood concentration， albumin and serum urea level （with odds ratios of 1.615， 1.538， 1.623， 1.942 and 0.637， respectively； 95% confidence intervals of 1.128-2.359， 1.059-2.251， 1.112-2.431， 1.106-3.598 and 0.402-0.980， respectively） were all significantly associated with VPA-induced hyperammonemia in neurocritical patients （ P ＜0.05）. The nomogram prediction model constructed based on these variables was evaluated， showing that the area under the ROC curve was 0.810 for the test set and 0.844 for the validation set. The calibration curves closely approximated t he actual curves， and the application of this model could improve the clinical net benefit. CONCLUSIONS Concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， high VPA blood concentration and high albumin level are independent risk factors for VPA-induced hyperammonemia in neurocritical patients， while high serum urea level is an independent protective factor. The risk prediction model constructed based on these factors exhibits good discrimination， consistency， and clinical applicability， making it applicable for predicting the risk of VPA-induced hyperammonemia in neurocritical patients.

Objective To investigate the diagnosis and treatment of 2 cases with spontaneous renal vascular rupture, and discuss the possible causes and treatment methods of this disease. Methods The clinical data and treatment methods of the 2 patients with spontaneous renal vascular rupture treated with renal artery embolization in Universal Global Xi'an Beihuan Hospital were analyzed. Relevant literature was reviewed to summarize the possible causes of this condition. Results The patients had no obvious history of trauma and no obvious abnormal coagulation function, and sought treatment due to sudden lumbar and abdominal pain. Laboratory tests revealed significantly decreased hemoglobin level, and elevated blood glucose (27.8, 27.6mmol/L). Abdominal computed tomography (CT) indicated perirenal hematoma and active bleeding. The bleeding arteries were located at the terminal branches of the anterior renal artery. Precise embolization was performed using CT angiography and selective renal artery angiography plus embolization, achieving an immediate hemostasis success rate of 100%. Postoperative hemoglobin level stabilized, and follow-up CT scans showed significant absorption of the perirenal hematoma without significant deterioration of renal function. Based on literature review and case analysis, the possible cause of spontaneous renal vascular rupture in these two patients was renal vascular sclerosis due to long-term diabetes. Other common etiologies of this condition included renal tumor, vascular malformation, and hypertension. Conclusion Spontaneous renal vascular rupture is rare. Renal artery embolization, as aminimally invasive treatment, can effectively control bleeding and protect renal function. The specific pathogenesis of this condition still requires further investigation. Long-term diabetes mellitus with poor blood glucose control may be associated factors, but more evidence is needed.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

OBJECTIVES: Anxiety is a common negative emotion. Under current social circumstances, university young teachers face multiple stressors and are more prone to anxiety, seriously threatening their physical and mental health. This study aims to investigate the impact of job insecurity on anxiety of university young teachers, while exploring the mediating roles of perceived stress and insomnia on this relationship. METHODS: Using convenience sampling, young teachers from a general university in a Chinese province were surveyed online. Scores of the Job Insecurity Scale, Perceived Stress Scale, Athens Insomnia Scale-Short Form, and Generalized Anxiety Disorder Scale were collected. A chain mediation analysis was conducted using the PROCESS macro. RESULTS: A total of 798 subjects were finally included. The detection rate of anxiety among university young teachers was 36.47%. Mediation analysis showed that job insecurity not only had a direct effect on anxiety, but also indirectly affected anxiety via perceived stress (46.42% of the total effect) and insomnia (7.45%), as well as through the chain-mediating path of perceived stress→ insomnia (13.18%; all P<0.05). CONCLUSIONS Job insecurity is a significant predictor of anxiety in young university faculty. Perceived stress and insomnia serve as sequential mediators in this relationship. Targeted interventions addressing job insecurity, stress perception, and sleep disturbances, alongside efforts to improve mental health literacy and the working environment, may help promote the overall well-being of university young teachers.
Humans ; Sleep Initiation and Maintenance Disorders/epidemiology* ; Universities ; Female ; Anxiety/psychology* ; Male ; Stress, Psychological/psychology* ; Adult ; Faculty/psychology* ; Surveys and Questionnaires ; China/epidemiology* ; Occupational Stress ; Job Security

BackgroundInsomnia， a common sleep disorder， is robustly associated with cardiovascular diseases， diabetes， and psychiatric disorders， substantially impairing quality of life. Although clinically commonly used medications are effective， long-term use may lead to drug resistance and dependence. While the efficacy of Ganmai Dazao Decoction in improving insomnia is definite， its underlying molecular mechanisms remain unclear. ObjectiveTo explore the active ingredients and core targets of Ganmai Dazao Decoction in the treatment of insomnia， systematically reveal its potential molecular pharmacological mechanism， and to provide references for clinical application. MethodsIn November 2024， the active ingredients and related targets of Ganmai Dazao Decoction were screened from the INPUT database. Insomnia-related datasets were acquired from the Gene Expression Omnibus （GEO） database， followed by differential expression analysis using GEO2R to identify differentially expressed genes （DEGs） associated with insomnia. The shared targets were obtained through Venn diagrams， and the protein-protein interaction （PPI） network was constructed using the STRING database and Cytoscape 3.9.1. Enrichment analyses were conducted on the shared targets using Gene Ontology （GO） and the Kyoto Encyclopedia of Genes and Genomes （KEGG）. The top 3 key active ingredients and the top 10 core targets in terms of node degree values were selected. Molecular docking and molecular dynamics simulation of receptors and ligands were performed using AutoDock 4.4.6， and the results were visualized using Pymol 3.0.3 to further verify the stability of the receptor-ligand complex system. ResultsA total of 337 active ingredients and 5 265 drug-related targets in Ganmai Dazao Decoction were retrieved， along with 1 061 insomnia-related DEGs. 287 shared targets were identified between Ganmai Dazao Decoction and insomnia. The traditional Chinese medicine-active ingredients-shared targets-disease network showed that quercetin， catechins and kaempferol were the key components of Ganmai Dazao Decoction in treating insomnia. These three components alleviate insomnia by acting on ten core targets， including nuclear factor kappa B inhibitor alpha （NFKBIA）， fibronectin 1 （FN1）， interleukin-6 （IL6）， protein c-Fos （FOS）， histone acetyltransferase p300 （EP300）， histone deacetylase 1 （HDAC1）， transcription factor Jun （JUN）， heat shock protein HSP 90-alpha 1 （HSP90AA1）， glyceraldehyde 3-phosphate dehydrogenase （GAPDH）， and interleukin-1 beta （IL1β）. GO and KEGG enrichment analyses indicated that Ganmai Dazao Decoction may alleviate insomnia through the IL17 signaling pathways， lipid and atherosclerosis signaling pathways， and other mechanisms. The results of molecular docking demonstrated strong binding affinity between the 3 key components and the 10 core targets of Ganmai Dazao Decoction. Molecular dynamics simulations further confirmed the stability of the quercetin-GAPDH， catechin-HDAC1 and kaempferol-EP300 complexes. ConclusionThe key components of Ganmai Dazao Decoction， namely quercetin， catechin， and kaempferol， exert therapeutic effects on insomnia by targeting 10 core proteins and modulating multiple pathways， including the IL17 signaling pathway， lipids and atherosclerotic-related pathways. ［Funded by Chengdu Medical College Level Scientific Research Project （number， CYZYB23-01）］

Objective:To assess common errors in head and neck CT angiography (CTA) image reports using four types of large language models (LLM), namely GPT-4, DeepSeek, ERNIE Bot and SparkDesk, and to assess the feasibility of using existing LLMs to support quality control of radiology reports in Chinese.Methods:The study was a cross-sectional study. Totally 1 000 head and neck CTA image reports were randomly selected using the simple random sampling method from Xuanwu Hospital, Capital Medical University in 2023, including 500 primary reports and 500 finalized reports. Two radiologists collaboratively identified six types of errors in the reports: description errors, writing errors, left-right confusion errors, diagnostic omissions, logical sequence errors, and other errors. The overall quality of the reports was assessed using a 5-point Likert scale. Subsequently, GPT-4, DeepSeek, ERNIE Bot and SparkDesk models were employed to detect the same six types of errors in the imaging reports and to provide overall scoring. The results from manual review were considered the gold standard for calculating F1 score to evaluate model performance. Intra-class correlation coefficients ( ICC) were used to assess the consistency between manual scores and the overall scores from the four LLMs. Results:In the primary imaging reports, the proportions of manually detected errors were as follows: descriptive errors 2.6% (13/500), writing errors 0.6% (3/500), left-right confusion errors 0, diagnostic omissions 6.4% (32/500), logical sequence errors 5.2% (26/500), and other errors 0. In the finalized imaging reports, the proportions of errors across the six categories were 0.2% (1/500), 0, 0, 0, 0, and 0.2% (1/500), respectively. For error detection in the primary imaging reports, the F1 scores of GPT-4 for the six error types were 0.992, 0.997, 0.997, 0.967, 0.980, and 0.992, respectively. DeepSeek achieved F1 scores of 0.980, 0.955, 0.981, 0.920, 0.995, and 0.960; ERNIE Bot scored 0.982, 0.990, 1.000, 0.956, 0.976, and 0.999; and SparkDesk achieved 0.985, 0.995, 1.000, 0.961, 0.982, and 1.000. In the detection of errors in finalized imaging reports, GPT-4′s F1 scores were 0.994, 0.995, 0.998, 0.973, 0.989, and 0.993; DeepSeek scored 0.968, 0.965, 0.985, 0.971, 0.991, and 0.983; ERNIE Bot achieved 0.996, 0.992, 1.000, 0.983, 0.999, and 0.997; and SparkDesk achieved 0.999, 0.999, 1.000, 1.000, 1.000, and 0.999. The consistency between GPT-4, DeepSeek, and SparkDesk models and human ratings was moderate, with ICC values of 0.514, 0.560, and 0.515 respectively (all P0.001); in contrast, the overall score of ERNIE Bot showed poor consistency with human ratings, with an ICC of 0.221 ( P0.001). Conclusion:LLMs demonstrate high accuracy in detecting errors in head and neck CTA imaging reports. The overall scoring of report quality shows moderate consistency with manual assessments, indicating a certain feasibility for automated quality control in reporting.

Colorectal cancer(CRC)is one of the most common malignant tumors worldwide,and its incidence and fatality rates rank at the forefront of malignant tumors.In recent years,with the maturity of laparoscopic and robotic technology,and the application of new staplers,the efficacy and safety of surgery for CRC have improved;however,postoperative complications still seriously affect postoperative quality of life and survival time.Identification of nutritional predictors of CRC is conducive to the early identification of high-risk patients,reinforce-ment of individualized care,enhancement of the quality of peri-operative management,reduction in the incidence of postoperative complic-ations,and improvement of the short-and long-term prognosis.In this paper,the literature on nutritional predictors of postoperative com-plications of CRC was reviewed,the evaluation contents and efficacy of nutritional predictors were summarized,and their advantages and disadvantages were analyzed.The aim is to provide a reference for identifying nutritional predictors of postoperative complications of CRC that are readily accessible,low-cost,and adjustable pre-operatively.

With the rapid development of the healthcare industry and the deepening implementation of the Healthy China strategy,high-quality development has become the core goal of China's healthcare service system construction.As an important component of the healthcare service system,research-oriented hospitals undertake multiple missions such as technological innovation,clinical translation,and talent cultivation.A team of communication experts and lead authors jointly participated in the compilation of the expert group's related expert team to comprehensively analyze the current development status,existing problems,and future directions of research-oriented hospitals in China.After inviting well-known experts in hospital management from across the country to discuss and exchange ideas,it proposed a consensus on the construction mode and path of research-oriented hospitals in China under high-quality development,aiming to further guide and standardize the current construction work of research-oriented hospitals in China,and provide reference for the formulation and practice of relevant policies at the national and provincial levels.

[Objective]To evaluate the utility of left atrial(LA)volume and strain measured by 4D auto left atrial quantification(4D auto LAQ)in differentiating pre-capillary from post-capillary pulmonary hypertension(PH),and to compare its discriminative performance with echocardiographic pulmonary to left atrial global strain ratio(ePLAGS).[Methods]A total of ninety-eight subjects with intermediate to high probability of PH were prospectively enrolled.Clinical history and laboratory data were collected.All patients underwent comprehensive transthoracic echocardiography,and LA volume and strain parameters were measured by dedicated commercial software for LA 4D analysis.[Results]Based on pulmonary arterial wedge pressure,patients were divided into pre-capillary PH group[n=39;mean age(53±24)years]and post-capillary PH group[n=59;mean age(57±18)years].Compared to the pre-capillary PH group,the post-capillary PH group showed significantly higher LAVImax,LAVImin and LAVIpreA but markedly lower LASr and LAScd.Multivariate logistic regression identified LAVImax[OR:1.40;95%CI:(1.052,1.872);P=0.021]and LAScd[OR:1.76;95%CI:(1.183,2.489);P=0.004]as independent predictors of post-capillary PH.ROC analysis demonstrated that LAVImax(AUC=0.82,P＜0.001)and LAScd(AUC=0.78,P＜0.001)had strong discriminating power for predicting post-capillary PH group,with optimal cutoff values of 35.69 mL/m2(sensitivity 86%,specificity 74%)and-9%(sensitivity 80%,specificity70%).[Conclusion]LAVImax and LAScd measured with 4D auto LAQ are robust parameters for distinguishing pre-capillary PH from post-capillary PH.

Knee osteoarthritis(KOA)is a prevalent chronic degenerative disorder among older adults,with biomechanical factors playing a crucial role in its pathogenesis and progression.This article aims to direct clinical studies on Tai Ji Quan(Shadow Boxing)therapeutic intervention for KOA by analyzing biomechanical factors in the pathogenesis of KOA and generalizing the biomechanical characteristics of Tai Ji Quan exercise and its impact on the gait pattern,overall mechanical balance,muscle function,plantar pressure,and proprioception of KOA patients,as well as summarizing the limitations in current clinical research.