Objective: To identify early clinical predictors associated with dysphagia and delayed swallowing recovery in patients with traumatic brain injury (TBI). Methods: In this retrospective study, we enrolled adult TBI patients admitted to the rehabilitation unit of a tertiary medical center between June 2019 and June 2023. Data on baseline characteristics, neurological status, imaging findings, and rehabilitation-related variables were collected. Swallowing function was assessed using two indicators: (1) nasogastric (NG) tube retention and (2) the Functional Oral Intake Scale (FOIS) scores at 1, 4, and 12 weeks post-injury. Regression analyses were conducted to identify predictors associated with dysphagia and swallowing recovery. Results: A total of 160 patients were included. At 1 week post-injury, longer intensive care unit (ICU) stay, poor initial sitting balance and use of sedative medication in ICU were associated with NG tube retention. At 4 weeks, lower initial Rancho Los Amigos Scale (RLAS) scores, immobility-related complications, longer hospitalization, and temporal lobe hematomas were associated with persistent NG tube dependence. By 12 weeks, older age, delayed ability to follow commands, and poor initial sitting balance remained associated with NG tube retention. FOIS outcomes were also associated with older age, delayed time to follow commands, impaired initial sitting balance, prolonged ICU stay, temporal lobe hematomas, lower initial RLAS scores, immobility-related complications, prolonged endotracheal tube placement and extended hospital stays. Conclusion Impaired cognitive status, poor physical function, immobility-related complications, and temporal lobe hematomas were key factors associated with dysphagia and delayed oral intake in individuals with TBI.

Objectives: . The prognostic value of the pretreatment albumin-to-alkaline phosphatase ratio (AAPR) in head and neck cancer (HNC) remains uncertain. This meta-analysis aimed to evaluate the predictive role of AAPR for survival outcomes in patients with HNC. Methods: . A comprehensive search of the Cochrane Library, PubMed, and Embase databases was conducted to identify relevant studies published up to July 30, 2024. We included studies on AAPR and survival outcomes in HNC patients. Results: . Eight studies comprising 1,737 HNC patients were analyzed using random-effects models. Lower AAPR values were significantly correlated with worse overall survival (hazard ratio [HR], 2.08), progression-free survival (HR, 2.00), and disease-free survival (HR, 2.18). Sensitivity analyses confirmed the robustness of these results, with no significant publication bias detected. Conclusion . Our findings suggest that pretreatment AAPR could serve as a valuable and cost-effective prognostic indicator in HNC, potentially aiding clinicians in risk stratification and treatment decision-making. However, additional validation studies are warranted to confirm its clinical applicability.

Circadian rhythm refers to the 24-hour periodic changes in behavior, physiology, and molecular processes in the human body. Disruptions to the circadian rhythm not only affect mental health but are also associated with various metabolic disorders, including the regulation of bone and muscle metabolism. Research has shown that work-related musculoskeletal disorders (WMSDs) are influenced not only by workload but also by circadian rhythm factors, such as shift work. This review examined the relationships between circadian rhythm-related antecedents, outcomes, and WMSDs, exploring their shared metabolic markers and mechanisms. It provided a systematic overview of the intrinsic connection between circadian rhythm disruptions and WMSDs. While current studies highlight the impact of circadian rhythm disturbances on musculoskeletal disorders, further investigation is required to address the confounding factors involved. Future research should integrate chronobiology with both subjective and objective data to explore the pathway from environmental factors to intermediate phenotypes to diseases, ultimately providing a more comprehensive understanding of the network mechanisms underlying WMSDs.

On August 24 2024, Xiaoshan District Center for Disease Control and Prevention, Hangzhou City, received a report of two cases of varicella infection among staff in the intensive care unit (ICU) of a hospital in its jurisdiction. The center immediately organized personnel to conduct an epidemiological investigation of the cases and their close contacts. The index case was a patient admitted to the ICU who had large areas of red rash and pustules on the chest, back, and right axilla. This case was diagnosed with herpes zoster by a dermatology consultation within the hospital. The other nine secondary cases were all nursing staff in the ICU, who were clinically diagnosed with varicella between August 21 and September 1, with an attack rate of 14.06%. All secondary varicella cases had a history of contact with the herpes zoster case and no history of varicella infection. Their varicella vaccination history was unknown. Based on the results of the on-site epidemiological and sanitary investigations, it was determined that this was an outbreak of varicella in the hospital caused by a herpes zoster case. After the last case was diagnosed, no new cases were reported within the longest incubation period (21 days), and the outbreak was declared over on September 21. Close contact with the herpes zoster case was likely the main cause of the outbreak. This highlights the need for early identification and isolation of suspected herpes zoster cases in hospitals in the future, as well as enhanced protective measures to prevent nosocomial infections.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Objective:Committee of Minimally Invasive Cardiovascular Surgery(CMICS) conducts an annual summary of minimally invasive cardiovascular surgery procedures performed throughout the country, which includes a comprehensive survey of the total number of minimally invasive procedures by region and the distribution of minimally invasive procedures by hospital. Since CMICS first published the 2018-2019 China Minimally Invasive Cardiovascular Surgery Data White Paper in 2020, the report has received great attention from peers within and outside the industry. In this statistical report, CMICS will focus on publishing the data related to minimally invasive cardiovascular surgery in China from 2021 to 2023 for reference and use by industry peers.

Objective:To analyze the clinical characteristics and prognosis of dengue fever inpatients in Guangzhou area, so that to provide references for clinical diagnosis and treatment.Methods:The demographic data, laboratory findings, clinical manifestations, and outcomes of 116 dengue fever cases admitted to Guangzhou Red Cross Hospital, Jinan University and the First Affiliated Hospital, Jinan University from August 1st to December 21st, 2024 were retrospectively analyzed.Results:Among the 116 patients, 99 cases (85.34%) were classified as non-severe dengue, while 17(14.66%) progressed to severe dengue (SD). The cohort was comprised of 62(53.45%) males and 54(46.55%) females, with an age of 63.5(22.0) years, and the hospitalization duration was 6(4) days, with the fever duration of 6(2) days. Sixty-two patients (53.45%) were complicated with comorbidities, among which hypertension (66.13%(41/62)), diabetes mellitus (25.81%(16/62)) and coronary atherosclerotic heart disease (22.58%(14/62)) accounted for the highest proportion. Primary clinical manifestations included fever (113 cases, 97.41%), with 86.21%(100/116) experiencing fever ≥five days, followed by fatigue (92 cases, 79.31%), myalgia (65 cases, 56.03%), anorexia (56 cases, 48.28%), cough/sputum (55 cases, 47.41%), and headache (54 cases, 46.55%). Early laboratory findings revealed leukopenia (2.22(1.75)×10 9/L], lymphopenia (0.63(0.50)×10 9/L), and thrombocytopenia (77.00(57.00)×10 9/L). Among 17 SD cases, 17 cases experienced severe organ damage, two cases had severe gastrointestinal bleeding, and two cases had septic shock. Among the patients with severe organ damage, there were eight cases of severe cardiac injury, followed by six cases of severe respiratory system injury, four cases of multiple organ dysfunction syndrome, three cases of acute kidney injury, three cases of neurological injury, and three cases of disseminated intravascular coagulation. Severe cardiac injury was manifested with acute heart failure in five cases, malignant arrhythmia in three cases, stress cardiomyopathy in one case, and acute myocardial infarction in one case. Severe respiratory system injuries were manifested with acute respiratory distress syndrome in five cases, severe pneumonia in three cases, and acute pulmonary embolism in one case. Neurological damage was manifested with viral meningitis in one case, acute cerebral infarction in one case, and sensorineural hearing loss in one case. All patients were cured or discharged after symptomatic supportive treatment and active prevention and treatment of complications. Conclusions:In 2024, dengue fever inpatients in Guangzhou area predominantly consist of elderly patients, who are complicated with comorbidities and present a high proportion of severe cases. Severe patients are primarily characterized by organ damage, with cardiovascular system injury being the most common severe manifestation. Dengue patients have a good prognosis.

AIM To study the chemical constituents from the roots of Siraitia grosvenorii(Swingle)C.Jeffrey and their α-glucosidase inhibitory activities.METHODS The 95％ethanol extract was isolated and purified by silica gel,MCI,ODS and HSCCC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The α-glucosidase inhibitory activities were evaluated by PNPG method,after which molecular docking was performed.RESULTS Twenty-one compounds were isolated and identified as vanillin(1),siraitic acid B(2),cucurbitacin B(3),salicylic acid(4),ferulic acid(5),p-hydroxybenzaldehyde(6),(+)-lariciresinol(7),(+)-isolariciresinol(8),liballinol(9),3-(hydroxyacetyl)indole(10),2E-4-hydroxy-nonenoic acid(11),vomifolilol(12),vanillic acid(13),indole-3-carboxylic acid(14),ω-hydroxypropioguaiacone(15),p-hydroxybenzoic acid(16),p-coumaric acid(17),dehydrodipinocarpine(18),secoisolariciresinol(19),sesquimarocanol A(20),threo-guaiacylglycerol-β-O-4-lariciresinol ether(21).IC50 values of compounds 4,10,18 and 21 were(0.42±0.060)-(0.89±0.037)mg/mL.CONCLUSION Compounds 4,10-12,15,16,18,and 21 are isolated from the roots of this plant for the first time.Compounds 4,10,18,21 have α-glucosidase inhibitory activities,and 18 has the strongest activity.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.