Objective To investigate the prevalence of cognitive frailty and its associated factors among middle-aged and elderly patients with chronic obstructive pulmonary disease (COPD) in Gusu District, Suzhou City, to provide a basis for intervention measures. Methods COPD patients managed at Pingjiang New Town Community Health Service Center in Gusu District from January to December 2024 were selected. Data were collected using the Fried Frailty Phenotype, Mini-Mental State Examination, and a general information questionnaire. Chi-square tests, one-way analysis of variance, and multivariate Logistic regression were used for data analysis. Results A total of 1 388 patients were included, with 916 males (65.99%) and 472 females (34.01%). Cognitive frailty was observed in 554 cases (prevalence: 39.91%). Univariate analysis showed significant differences in gender, education, visual impairment, hearing impairment, sleep disorders, and disease duration between the cognitive frailty and non-cognitive frailty groups (all P<0.05). Multivariate Logistic regression indicated that education was negatively associated with cognitive frailty (illiteracy OR=6.969, P<0.001; primary school OR=1.499, P=0.005), while visual impairment (OR=2.347, P<0.001), hearing impairment (OR=1.705, P<0.001), sleep disorders (OR=2.488, P<0.001), and disease duration (≤5 years OR=0.329, P<0.001; 6-10 years OR=0.487, P<0.001) were positively associated with cognitive frailty. Conclusion The prevalence of cognitive frailty among middle-aged and elderly COPD patients in Gusu District, Suzhou City, is high (39.91%). Epositively associated with cognitive frailtyducation, sensory impairments, sleep disorders, and disease duration are associated factors. Clinical attention to high-risk groups and implementation of early screening and targeted interventions are recommended.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

BACKGROUND:Exosomes derived from human umbilical cord mesenchymal stem cells are widely used for bone repair and reconstruction,significantly enhancing osteogenesis and promoting angiogenesis.OBJECTIVE:To explore the mechanisms of exosomes derived from human umbilical cord mesenchymal stem cells in the treatment of osteoporotic fractures.METHODS:H uman umbilical cord mesenchymal stem cells were extracted using tissue block culture method.Exosomes derived from human umbilical cord mesenchymal stem cells were extracted using ultracentrifugation method for identification.Thirty 12-week-old female SD rats were randomly divided into sham-operated group(n=6)and ovariectomized group(n=24).Osteoporosis model was established by castration in the ovariectomized group.12 weeks after modeling,6 rats in the ovariectomized group and 6 rats in the sham-operated group were randomly selected for Micro-CT and hematoxylin-eosin staining to verify the models.After verification,the remaining 18 rats in the ovariectomized group were randomly assigned to three groups to establish osteoporotic fracture models.The fracture end was separately injected with PBS(PBS group),exosomes at 1.5×1011 particles/mL(low-concentration exosome group),and 3×1011 particles/mL(high-concentration exosome group).Four weeks after operation,fracture healing and bone angiogenesis were evaluated by imaging and histological observations.RESULTS AND CONCLUSION:(1)In the gross specimens,compared with the PBS group,the exosome group had faster fracture healing and more callus formation.(2)The X-ray score of fracture healing in the exosome group was significantly higher than that in the PBS group,and the difference was significant(P＜0.05).(3)Micro-CT three-dimensional imaging:Compared with the PBS group,the fracture healing in the exosome group was accelerated and the callus formation was significantly increased;the bone volume fraction in the exosome group was significantly higher than that in the PBS group,and the difference was significant(P＜0.01).(4)Hematoxylin-eosin staining and Masson's trichrome staining showed that bone trabeculae and the new bone tissue in the exosome group were more than those in the PBS group.(5)Immunohistochemical staining showed that the expression of CD31 and osteocalcin in the exosome group was significantly higher than that in the PBS group.The high-concentration exosome group had a higher density of new blood vessels,more callus formation,and faster fracture healing than the low-concentration exosome group,showing a concentration-dependent manner.The results show that exosomes derived from human umbilical cord mesenchymal stem cells can promote the repair of osteoporotic fracture by enhancing the angiogenesis and osteogenesis.The mechanism may be related to the increased expression of CD31 and osteocalcin.

Objective To analyse the service status of telemedicine in a prefecture-level city public Grade-3A hospital,explore the role of telemedicine in the region,and provide suggestions for the sustainable development of telemedicine.Methods Retrospectively analyse the trend of demographic information changes of remote consultation patients from 2018 to 2024,exami-ning the distribution of remote consultation departments and the application for remote consultation hospitals.We also analyse the waiting time of patients'remote consultation,the composition of remote consultation experts and other data.Results During the period of 7 years,669 patients received remotely through the telemedicine centre platform.Among them,there were 364 cases for men and 305 cases for women;the average age was 50.29 years old.In 2021,the number of patients applying for telemedicine consultation reached peaked at 140.The top five departments utilizing telemedicine were Department of Imaging,Department of Critical Care Medicine,Nephrology,Urology and Department of Infectious Diseases.Telemedicine waiting time≤24 h accounts for 70.1% (469/669),while 81.76% (547/669)were seen within≤48 h,and 70% of patients can consult within 24 h.Among the experts who applied for telemedicine,there were,109 well-known experts(16.29% ,109/669),418 chief physi-cians(62.48% ,418/669),and 141 deputy chief physicians(21.08% ,141/669).Conclusion Telemedicine provide pa-tients with a comprehensive,convenient and efficient medical service method,helping to alleviate the uneven distribution of medi-cal resources,while enhancing the accessibility and quality of medical services.

OBJECTIVE: To investigate hypertension (HTN) trends, key risk factors, and gender disparities in rural China, and to propose targeted strategies for improving HTN control in resource-limited settings. METHODS: This longitudinal study used data from the Henan Rural Cohort Study, including baseline (2015-2017; n = 39,224) and follow-up (2018-2022; n = 28,621) participants. HTN was defined as systolic/diastolic blood pressure ≥ 140/90 mmHg, self-reported diagnosis, or use of antihypertensive medication. Severity was classified using a 7-tier blood pressure (BP) staging system (optimal, normal, high normal, and HTN stages 1-4). A generalized linear mixed-effects model (GLMM) identified associated risk factors. RESULTS: HTN prevalence increased modestly from 32.7% (95% CI: 32.2-33.2) to 33.9% (95% CI: 33.3%-34.4%). Awareness and treatment improved from 20.1% to 25.3%, and from 18.8% to 24.4%, respectively, but control rates remained low (6.2% to 12.3%). After adjustment, women had a 1.53-fold higher HTN risk than men ( OR = 1.53, 95% CI: 1.43-1.63), revealing gender-specific trends. Key risk factors included alcohol use ( OR = 1.37, 95% CI: 1.27-1.47) and overweight status ( OR = 1.76, 95% CI: 1.66-1.86). BP staging showed an increase in optimal BP (42.3% to 45.8%), but stagnant management of advanced HTN stages. CONCLUSION Hypertension in rural China is shaped by behavioral risk factors and healthcare access gaps. Gender-sensitive, community-based interventions, including task-shifting models, are necessary to mitigate the growing burden of hypertension.
Humans ; Hypertension/etiology* ; China/epidemiology* ; Female ; Male ; Rural Population/statistics & numerical data* ; Prevalence ; Risk Factors ; Middle Aged ; Adult ; Aged ; Longitudinal Studies ; Sex Factors ; Cohort Studies ; East Asian People

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.